Dust Emission Model Research Articles

The Roles of Morphology and Environment on the Star Formation Rate–Stellar Mass Relation in COSMOS from 0 < z < 3.5

We investigate the relationship between environment, morphology, and the star formation rate (SFR)–stellar mass relation derived from a sample of star-forming (SF) galaxies (commonly referred to as the “star formation main sequence”, SFMS) in the COSMOS field from 0 < z < 3.5. We constructed and fit the far-UV–far-IR spectral energy distributions of our stellar-mass-selected sample of 111,537 galaxies with stellar and dust emission models using the public packages MAGPHYS and SED3FIT. From the best-fit parameter estimates, we construct the SFR–stellar mass relation as a function of redshift, local environment, NUVrJ color diagnostics, and morphology. We find that the shape of the main sequence derived from our color–color and specific-star-formation-rate-selected SF galaxy population, including the turnover at high stellar mass, does not exhibit an environmental dependence at any redshift from 0 < z < 3.5. We investigate the role of morphology in the high-mass end of the SFMS to determine whether bulge growth is driving the high-mass turnover. We find that SF galaxies experience this turnover independent of bulge-to-total ratio, strengthening the case that the turnover is due to the disk component’s specific SFR evolving with stellar mass rather than bulge growth.

Generative Models of Multichannel Data from a Single Example—Application to Dust Emission

The quest for primordial B-modes in the cosmic microwave background has emphasized the need for refined models of the Galactic dust foreground. Here we aim at building a realistic statistical model of the multifrequency dust emission from a single example. We introduce a generic methodology relying on microcanonical gradient descent models conditioned by an extended family of wavelet phase harmonic (WPH) statistics. To tackle the multichannel aspect of the data, we define cross-WPH statistics, quantifying non-Gaussian correlations between maps. Our data-driven methodology could apply to various contexts, and we have updated the software PyWPH, on which this work relies, accordingly. Applying this to dust emission maps built from a magnetohydrodynamics simulation, we construct and assess two generative models: (1) a (I, E, B) multi-observable input, and (2) a multifrequency input. The samples exhibit consistent features compared to the original maps. A statistical analysis of model 1 shows that the power spectra, distributions of pixels, and Minkowski functionals are captured to a good extent. We analyze model 2 by fitting the spectral energy distribution (SED) of both the synthetic and original maps with a modified blackbody (MBB) law. The maps are equally well fitted, and a comparison of the MBB parameters shows that our model succeeds in capturing the spatial variations of the SED from the data. Besides the perspectives of this work for dust emission modeling, the introduction of cross-WPH statistics opens a new avenue to characterize non-Gaussian interactions across different maps, which we believe will be fruitful for astrophysics.

JWST Imaging of the Cartwheel Galaxy Reveals Dust Associated with SN 2021afdx

We present near- and mid-infrared (0.9–18 μm) photometry of supernova (SN) 2021afdx, which was imaged serendipitously with the James Webb Space Telescope (JWST) as part of its Early Release Observations of the Cartwheel Galaxy. Our ground-based optical observations show it is likely to be a Type IIb SN, the explosion of a yellow supergiant, and its infrared spectral energy distribution (SED) ≈200 days after explosion shows two distinct components, which we attribute to hot ejecta and warm dust. By fitting models of dust emission to the SED, we derive a dust mass of , which is the highest yet observed in a Type IIb SN but consistent with other Type II SNe observed by the Spitzer Space Telescope. We also find that the radius of the dust is significantly larger than the radius of the ejecta, as derived from spectroscopic velocities during the photospheric phase, which implies that we are seeing an infrared echo off of preexisting dust in the progenitor environment, rather than dust newly formed by the SN. Our results show the power of JWST to address questions of dust formation in SNe, and therefore the presence of dust in the early universe, with much larger samples than have been previously possible.

The uncertain interstellar medium of high-redshift quiescent galaxies: Impact of methodology

How much gas and dust is contained in high-redshift quiescent galaxies (QGs) is currently an open question with relatively few and contradictory answers, as well as important implications for our understanding of the nature of star formation quenching processes at cosmic noon. Here we revisit far-infrared (FIR) observations of the REQUIEM-ALMA sample of six z = 1.6 − 3.2 QGs strongly lensed by intermediate-redshift galaxy clusters. We measured their continuum emission using priors obtained from high resolution near-infrared (NIR) imaging, as opposed to focusing on point-source extraction, converted it into dust masses using a FIR dust emission model derived from statistical samples of QGs, and compared the results to those of the reference work. We find that, while at least the most massive sample galaxy is indeed dust-poor, the picture is much more nuanced than previously reported. In particular, these more conservative constraints remain consistent with high dust fractions in early QGs. We find that these measurements are very sensitive to the adopted extraction method and conversion factors: the use of an extended light model to fit the FIR emission increases the flux of detections by up to 50% and the upper limit by up to a factor 6. Adding the FIR-to-dust conversion, this amounts to an order of magnitude difference in dust fraction, casting doubts on the power of these data to discriminate between star formation quenching scenarios. Unless these are identified by other means, mapping the dust and gas in high-redshift QGs will continue to require somewhat costly observations.

AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio

We present a comprehensive census of the active galactic nuclei (AGNs) in the GOODS-S/HUDF region from the X-ray to the radio, covering both the obscured and unobscured populations. This work includes a robust analysis of the source optical to mid-IR spectral energy distributions (SEDs) featuring (semi)empirical AGN and galaxy dust emission models and Bayesian fitting techniques, ultra-deep Very Large Array 3 and 6 GHz observations, and an integrated analysis of various AGN selection techniques, including X-ray properties, UV to mid-IR SED analysis, optical spectral features, mid-IR colors, radio-loudness and spectral slope, and AGN variability. In total, we report ∼900 AGNs over the ∼170 arcmin2 3D-HST GOODS-S footprint, which has doubled the AGN number identified in the previous X-ray sample, with ∼26% of our sample undetected in the deepest Chandra image. With a summary of AGN demographics from different selection methods, we find that no one single band or technique comes close to selecting a complete AGN sample despite the great depth of the data in GOODS-S/HUDF. We estimate the yields of various approaches and explore the reasons for incompleteness. We characterize the statistical properties, such as source number density, obscuration fraction, and luminosity function of the AGN sample in this field, and discuss their immediate implications. We also provide some qualitative predictions of the AGN sample that might be discovered by the upcoming JWST surveys.

Drivers of recent decline in dust activity over East Asia

It is essential to understand the factors driving the recent decline of dust activity in East Asia for future dust projections. Using a physically-based dust emission model, here we show that the weakening of surface wind and the increasing of vegetation cover and soil moisture have all contributed to the decline in dust activity during 2001 to 2017. The relative contributions of these three factors to the dust emission reduction during 2010–2017 relative to 2001 are 46%, 30%, and 24%, respectively. Much (78%) of the dust emission reduction is from barren lands, and a small fraction (4.6%) of the reduction is attributed to grassland vegetation increase that is partly ascribed to the ecological restoration. This suggests that the ecological restoration plays a minor role in the decline of dust activity. Rather, the decline is mainly driven by climatic factors, with the weakening of surface wind playing the dominant role.

Modeling dust emission in alpine regions with low air temperature and low air pressure – A case study on the Qinghai-Tibetan Plateau (QTP)

• Variations of temperature and pressure could impact dust emission process. • Air density is an important parameter in dust emission modeling. • The improved model could simulate precisely the dust emission in the QTP. • The dust emission in the QTP mainly occurred in winter and early spring. Dust emission is one of the important segments of the circulation of materials between lithosphere, atmosphere, and ocean systems. However, studies on dust emission have mainly concentrated on arid and semiarid regions with few studies focused on dust emission in alpine areas, where having lower air temperatures and lower air pressure environments. The lower air temperature and lower air pressure could significantly impact the air density and make the entrainment and transport of dust different from those at lower altitudes. The lack of accurate studies on dust emission in alpine regions has resulted in large uncertainties in the global dust budget and brought large challenges in controlling aeolian hazards in alpine regions. To bridge this gap, we took the air density as an important parameter to simulate dust emission in the Qinghai-Tibetan Plateau (QTP), where has typical low air-temperature and low air-pressure environments. The measured data showed that the lower air temperature and low air pressure affect the particle size distributions (PSDs) of aeolian sediment, the threshold velocity (TFV) as well as the dust emission rate. Herein, we introduced air density as an important factor to improve a dust emission model, and the validated results showed that the deviations of the simulated horizontal sand flux and vertical dust flux were less than 30% and 35%, respectively. Using the improved model, we could exactly depict the spatial and temporal distribution of dust emission in the QTP. The results shown, our model could exactly depict the spatial and temporal distribution of dust emission in the QTP. We believe that the improvement of the model could offer a new perspective on dust emission in environments with lower air temperature and lower air pressure, and the simulated results could provide valuable data for global dust budget estimation.

Properties of shocked dust grains in supernova remnants

ABSTRACT Shockwaves driven by supernovae both destroy dust and reprocess the surviving grains, greatly affecting the resulting dust properties of the interstellar medium (ISM). While these processes have been extensively studied theoretically, observational constraints are limited. We use physically motivated models of dust emission to fit the infrared (IR) spectral energy distributions of seven Galactic supernova remnants, allowing us to determine the distribution of dust mass between diffuse and dense gas phases, and between large and small grain sizes. We find that the dense ($\sim \! 10^3\ {\rm cm}^{-3}$), relatively cool ($\sim \! 10^3\ {\rm K}$) gas phase contains $\gt 90{{\ \rm per\ cent}}$ of the dust mass, making the warm dust located in the X-ray emitting plasma ($\sim \! 1\ {\rm cm}^{-3}$/$10^6\ {\rm K}$) a negligible fraction of the total, despite dominating the mid-IR emission. The ratio of small ($\lesssim\!{10}\ {\rm nm}$) to large ($\gtrsim \! 0.1\ {\rm \mu m}$) grains in the cold component is consistent with that in the ISM, and possibly even higher, whereas the hot phase is almost entirely devoid of small grains. This suggests that grain shattering, which processes large grains into smaller ones, is ineffective in the low-density gas, contrary to model predictions. Single-phase models of dust destruction in the ISM, which do not account for the existence of the cold swept-up material containing most of the dust mass, are likely to greatly overestimate the rate of dust destruction by supernovae.

Mitigating Bias in CMB B-modes from Foreground Cleaning Using a Moment Expansion

One of the primary challenges facing upcoming cosmic microwave background (CMB) polarization experiments aiming to measure the inflationary B-mode signal is the removal of polarized foregrounds. The thermal dust foreground is often modeled as a single modified blackbody; however, overly simplistic foreground models can bias measurements of the tensor-to-scalar ratio r. As CMB polarization experiments become increasingly sensitive, thermal dust emission models must account for greater complexity in the dust foreground while making minimal assumptions about the underlying distribution of dust properties within a beam. We use Planck dust temperature data to estimate the typical variation in dust properties along the line of sight and examine the impact of these variations on the bias in r if a single modified blackbody model is assumed. We then assess the ability of the moment method to capture the effects of spatial averaging and to reduce bias in the tensor-to-scalar ratio for different possible toy models of dust emission. We find that the expected bias due to temperature variations along the line of sight is significant compared to the target sensitivities of future CMB experiments, and that the use of the moment method could reduce bias as well as shed light into the distribution of dust physical parameters.

Gas and Cosmic-Ray Properties in the MBM 53, 54, and 55 Molecular Clouds and the Pegasus Loops Revealed by H i Line Profiles, Dust, and Gamma-Ray Data

In studying the interstellar medium (ISM) and Galactic cosmic rays (CRs), uncertainty of the interstellar gas density has always been an issue. To overcome this difficulty, we used a component decomposition of the 21 cm H i emission line and used the resulting gas maps in an analysis of γ-ray data obtained by the Fermi Large Area Telescope (LAT) for the MBM 53, 54, and 55 molecular clouds and the Pegasus loop. We decomposed the ISM gas into intermediate-velocity clouds, narrow-line and optically thick H i, broad-line and optically thin H i, CO-bright H2, and CO-dark H2 using detailed correlations with the H i line profiles from the HI4PI survey, the Planck dust-emission model, and the Fermi-LAT γ-ray data. We found the fractions of the optical depth correction to the H i column density and CO-dark H2 to be nearly equal. We fitted the CR spectra directly measured at/near the Earth and the measured γ-ray emissivity spectrum simultaneously. We obtained a spectral break in the interstellar proton spectrum at ∼7 GeV, and found that the γ-ray emissivity normalization agrees with the AMS-02 proton spectrum within 10%, relaxing the tension with the CR spectra previously claimed.

Suppression Effect of Waterborne Polymer on Soil Used for Backfilling at Construction Site

To improve the dust control efficiency of soil for backfilling at construction sites, a novel waterborne polymer was used as a dust suppressant, and the dust emission model was created to control the effect of a large-scale field. The results showed that the waterborne polymer could improve the water retention efficiency of soil for backfilling, and the average water content was 2.18 times that of the watered samples, significantly delaying water evaporation. The compressive strength of soil for backfilling reached 4.91 MPa and improved the wind erosion resistance of the consolidation layer, effectively resisting wind damage. At a construction site, the waterborne polymer was sprayed on soil for backfilling, and the concentration of PM10 was reduced by 67.41%, confirming the effectiveness for large-scale utilization.

Wind-tunnel experiments of Aeolian sand transport reveal a bimodal probability distribution function for the particle lift-off velocities

The probability distribution function (PDF) of the lift-off velocities of Aeolian (wind-blown) sand particles – i.e., the velocities with which the particles rebound or are ejected from the bed owing to a granular-bed collision – is an important parameter in models of sediment transport and dust emission. However, in order to reliably describe this distribution function, measurements of the individual particle trajectories near the sand bed during sediment transport are required. Such measurements are challenging due to the high particle concentration near the bed, which makes it difficult to track the dynamics of the particles involved in the lift-off process. Here we seek to overcome this difficulty by applying an experimental method for grain trajectory detection, which allows us to obtain a large number of near-bed lift-off particle trajectories during sand transport in a boundary layer wind tunnel.The PDFs of horizontal and vertical lift-off velocities all were found to display a bimodal distribution at a height smaller than 1 mm from the bed. The first and second maxima in the distribution curve of horizontal and vertical lift-off velocities occur at around 0.25 and 1.0 ms−1, and at 0 and 1.0 ms−1, respectively. Moreover, the first maximum is mainly associated with splashed particles, whereas the second peak is mainly caused by rebound particles. However, the lift-off velocities far from the bed follow a unimodal distribution, in agreement with previous experiments. Our results are providing, thus, unprecedented insights about near-bed transport processes over wind-blown soils, and have implication for modelling granular-bed interactions in Aeolian sand transport and geomorphodynamic models.

On the simultaneous modelling of dust and stellar populations for interpretation of galaxy properties

ABSTRACT The physical properties of galaxies are encoded within their spectral energy distribution and require comparison with models to be extracted. These models must contain a synthetic stellar population and, where infrared data are to be used, also consider prescriptions for energy reprocessing and re-emission by dust. While many such models have been constructed, there are few analyses of the impact of stellar population model choice on derived dust parameters, or vice versa. Here, we apply a simple framework to compare the impact of these choices, combining three commonly used stellar population synthesis models and three dust emission models. We compare fits to the ultraviolet to far-infrared spectral energy distributions of a validation sample of infrared-luminous galaxies. We find that including different physics, such as binary stellar evolution, in the stellar synthesis model can introduce biases and uncertainties in the derived parameters of the dust and stellar emission models, largely due to differences in the far-ultraviolet emission available for reprocessing. This may help to reconcile the discrepancy between the cosmic star formation rate and stellar mass density histories. Notably the inclusion of a dusty stellar birth cloud component in the dust emission model provides more flexibility in accommodating the stellar population model, as its re-emission is highly sensitive to the ultraviolet radiation field spectrum and density. Binary populations favour a longer birth cloud dissipation time-scale than is found when assuming only single star population synthesis.

Full-sky, Arcminute-scale, 3D Models of Galactic Microwave Foreground Dust Emission Based on Filaments

Abstract We present the DustFilaments code, a full-sky model for the millimeter Galactic emission of thermal dust. Our model, composed of millions of filaments that are imperfectly aligned with the magnetic field, is able to reproduce the main features of the dust angular power spectra at 353 GHz as measured by the Planck mission. Our model is made up of a population of filaments with sizes following a Pareto distribution ∝ L a − 2.445 , with an axis ratio between short and long semiaxes ϵ ∼ 0.16 and an angle of magnetic field misalignment with a dispersion rms(θ LH) = 10°. On large scales, our model follows a Planck-based template. On small scales, our model produces spectra that behave like power laws up to ℓ ∼ 4000 or smaller scales by considering even smaller filaments, limited only by computing power. We can produce any number of Monte Carlo realizations of small-scale Galactic dust. Our model will allow tests of how the small-scale non-Gaussianity affects CMB weak lensing and the consequences for the measurement of primordial gravitational waves or relativistic light relic species. Our model also can generate frequency decorrelation on the modified blackbody spectrum of dust and is freely adjustable to different levels of decorrelation. This can be used to test the performance of component separation methods and the impact of frequency spectrum residuals on primordial B-mode surveys. The filament density we paint in the sky is also able to reproduce the general level of non-Gaussianities measured by Minkowski functionals in the Planck 353 GHz channel map.

Using the Optical–NIR Spectral Energy Distributions to Search for the Evidence of Dust Formation of 66 Supernovae

Abstract In this paper, we searched for the dust formation evidence of 66 supernovae (SNe) by using the blackbody model and the blackbody plus dust emission model to fit their early-time optical–near-infrared (NIR) spectral energy distributions (SEDs). We find that, while the blackbody model can fit most SEDs of the SNe in our sample, the model cannot fit the SEDs of some SNe in which the SEDs of two SNe (SNe 2010bq and 2012ca) show NIR excesses which can be attributed to the emission from the heated dust. We use the blackbody plus dust emission model to fit the SEDs showing NIR excesses, finding that both the graphite and silicate dust models can fit the SEDs, and the graphite model gets reasonable temperatures or better fits. Assuming that the dust is graphite, the best-fitting temperatures (masses) of the dust of SNe 2010bq and 2012ca are ∼1300–1800 K (∼0.1–3.4 ×10−4 M ⊙) and ∼600–1000 K (∼0.6–7.5 × 10−3 M ⊙), respectively. We compare the vaporization radii and the blackbody radii of the dust shells of the two SNe with the upper limits of the ejecta radii of the SNe at the first epochs, and demonstrate that the NIR excesses of the SEDs of the two SNe might be caused by the pre-existing dust.

Where and How Often Does Rain Prevent Dust Emission?

AbstractPrecipitation‐derived soil moisture in the active aeolian layer (the top ∼2 mm of the soil) impacts dust emission by increasing the threshold for emission. The purpose of this study was to use data similar to those used in global and regional dust emission models to calculate the probability that a high wind event happens during the period that antecedent precipitation would have left the active layer wet. The results indicate that the answer to this question is more strongly related to regional climate than soil texture. For more than half of the global drylands, the probability of precipitation influencing dust emission is greater than 30%–40%. Thus, rain‐derived soil moisture in the active layer should not be ignored in models throughout much of the world's dust producing regions. However, because the thin active layer dries faster than the underlying soil, models that use thick surface soil layer moisture for this may underestimate dust emission.

Parameterizing an aeolian erosion model for rangelands

Aeolian processes are fundamental to arid and semi-arid ecosystems, but modeling approaches are poorly developed for assessing impacts of management and environmental change on sediment transport rates over meaningful spatial and temporal scales. For model estimates to provide value, estimates of sediment flux that encapsulate intra- and inter-annual and spatial variability are needed. Further, it is important to quantify and communicate transparent estimates of model uncertainty to users. Here, we present a wind erosion and dust emission model parameterized for rangelands using a Generalized Likelihood Uncertainty Estimation framework. Modeled horizontal sediment flux was calibrated using data from five diverse grassland and shrubland sites from the USDA National Wind Erosion Research Network. Observations of wind speed, vegetation height, length of gaps between vegetation, and percent bare ground were used as model inputs. Horizontal sediment flux estimates from 10,000 independently selected parameter sets were compared to flux observations from 44 ∼ month-long collection periods to calculate a likelihood measure for each model. Results show good agreement for individual sampling periods across sites with few observations falling outside prediction bounds and a one-to-one relationship between median predictions and observations. Additionally, combined distributions of sediment flux estimates from all sample periods for a given site closely approximated the probability of observing a given flux at that site. These results suggest AERO effectively represents temporal variability in aeolian transport rates at rangeland sites and provides robust assessments suitable for assessing land health and better predicting changes in air quality and the impacts of land management activities.

Dust destruction and survival in the Cassiopeia A reverse shock

ABSTRACT Core-collapse supernovae (CCSNe) produce large ($\gtrsim0.1\,{\rm M}_\odot$) masses of dust, and are potentially the primary source of dust in the Universe, but much of this dust may be destroyed before reaching the interstellar medium. Cassiopeia A (Cas A) is the only supernova remnant where an observational measurement of the dust destruction efficiency in the reverse shock is possible at present. We determine the pre- and post-shock dust masses in Cas A using a substantially improved dust emission model. In our preferred models, the unshocked ejecta contains $0.6\!-\!0.8\,{\rm M}_\odot$ of $0.1\,{\rm \mu m}$ silicate grains, while the post-shock ejecta has $0.02\!-\!0.09\,{\rm M}_\odot$ of $5\!-\!10 \, {\rm nm}$ grains in dense clumps, and $2 \times 10^{-3}\,{\rm M}_\odot$ of $0.1 \, {\rm \mu m}$ grains in the diffuse X-ray emitting shocked ejecta. The implied dust destruction efficiency is $74\!-\!94\,{\rm per\,cent}$ in the clumps and $92\!-\!98\,{\rm per\,cent}$ overall, giving Cas A a final dust yield of $0.05\!-\!0.30\,{\rm M}_\odot$. If the unshocked ejecta grains are larger than $0.1\,{\rm \mu m}$, the dust masses are higher, the destruction efficiencies are lower, and the final yield may exceed $0.5\,{\rm M}_\odot$. As Cas A has a dense circumstellar environment and thus a much stronger reverse shock than is typical, the average dust destruction efficiency across all CCSNe is likely to be lower, and the average dust yield higher. This supports a mostly stellar origin for the cosmic dust budget.

Seasonal source identification and source-specific health risk assessment of pollutants in road dust.

Humans who are exposed to metals in road dust may have potential health risks through touching, ingesting, and inhaling the suspended road dust. There were limited studies to link seasonal emission sources to health risks from metals in road dust. In this study, metals in road dust from different functional areas were seasonally monitored. The contributions of the pollutant sources in study areas varied with seasons. By combining the source apportionment model (PMF), road dust emission model, and health risk models (HI: hazard index and ILCR: incremental lifetime carcinogenic risk), industrial and construction activity was identified as the crucial source of both the pollutants in road dust (29-47%), and the HI for adults (27-45%) and children (41-50%) in different seasons. The traffic non-exhaust emission dominated in the carcinogenic risks for children in spring (45%) and summer (36%). Factors such as seasons, particle size, metal bioavailability, human exposure time, and exposure area were all taken into consideration to avoid overestimating or underestimating health risks. The carcinogenic risks for children (1.6 E-06) and adults (2.8 E-06) exposed to Cr both exceed the minimum threshold (10-6). It means that the potential risks were acceptable but could not be completely neglected. Measured metals mainly posed hazard to human health through ingestion route. Pb and Mn, Fe and Mn were the main harmful elements that induced non-carcinogenic risks for adults and children, respectively. Effectively identifying the source-specific health risks in different seasons will help in the formulation of adaptive strategies to diminish the potential risks.

Quantifying the impact of cropland wind erosion on air quality: A high-resolution modeling case study of an Arizona dust storm

Dust storms fueled by wind erosion of desert and cropland soils in south-central Arizona have caused numerous highway accidents and health risks by creating hazardous air quality conditions. Despite much speculation that a major fraction of windblown dust during these storms originates at an active or abandoned cropland surface over the region, its quantification is largely missing in the literature. This study estimated the contribution of cropland wind erosion to the regional air quality degradation, in terms of concentration of particulate matter with diameter 10 μm and smaller (PM10), during a typical springtime dust storm, by conducting high-resolution (1 km horizontally) simulations utilizing the Weather Research and Forecasting-FENGSHA (a dust emission model)-Community Multiscale Air Quality (WRF-FENGSHA-CMAQ) modeling framework. The dust model for this study employed up-to-date and very high-resolution data on land use, soil texture, and vegetation index. The modeling system used in this study simulated reasonably well a regional dust storm (that raised concerns for air quality and highway safety) of 08–09 April 2013 compared against ground (station) observations of PM10 and satellite observations of dust optical depth and vertical structure of aerosol subtypes. The model evaluations also included the use of radar observations.Furthermore, the model results from this study revealed that the cropland wind erosion was responsible for 55% and 51% of total PM10 over Phoenix (33.35°N–33.85°N, 112.36°W–111.485°W) and western Pinal County (32.50°N–33.35°N, 112.2°W–111.2°W), respectively, during the simulated dust storm. The large contributions suggest that the inclusion and accurate representation of cropland dust sources are crucial in preparing emission inventories and in air quality modeling for the region. Such representation is particularly important in view of the projected future aridity over this region (that is already under a long-term drought), which may lead to fallowing of currently active farmlands, making them potential hotspots of dust emission. The modeling approach developed for this work can be used to carry out more comprehensive studies, over extended spatial and temporal extents, to identify the sources of windblown dust and quantify their climatological dust emission potentials for this region or elsewhere. Such studies are highly desirable to help decision-making processes to reduce windblown dust and the associated health and safety risks.