Sensitivities of the backscattering properties to the microphysical properties (in particular, size and shape) of mineral dust aerosols are examined based on TAMUdust2020, a comprehensive ...single‐scattering property database of irregular aerosol particles. We develop the bulk mineral dust particle models based on size‐resolved particle ensembles with randomly distorted shapes and spectrally resolved complex refractive indices, which are constrained by using in situ observations reported in the literature. The light detection and ranging (lidar) ratio is more sensitive to particle shape than particle size, while the depolarization ratio depends strongly on particle size. The simulated bulk backscattering properties (i.e., the lidar ratio and the depolarization ratio) of typical mineral dust particles with effective radii of 0.5–3 µm are reasonably consistent with lidar observations made during several field campaigns. The present dust bulk optical property models are applicable to lidar‐based remote sensing of dust aerosol properties.
Plain Language Summary
Light detection and ranging (Lidar) measurements help investigate atmospheric mineral dust aerosol properties. However, it has long been a challenge to interpret lidar signals, namely the backscattering properties, toward inferring mineral dust particle properties. This study is aimed to develop appropriate bulk mineral dust optical property models for simulating the backscattering properties. The present simulations demonstrate the significant impacts of mineral dust particle shape and size on backscattering by these particles. The developed mineral dust particle models will benefit lidar‐based remote sensing of mineral dust plumes.
Key Points
Bulk dust backscattering property models are developed at light detection and ranging (lidar) wavelengths
The lidar ratio is more sensitive to particle shape than to particle size
Simulated backscattering properties are reasonably consistent with lidar observations of dust plumes
Impacts of small‐scale surface irregularities, or surface roughness, of atmospheric ice crystals on lidar backscattering properties are quantified. Geometric ice crystal models with various degrees ...of surface roughness and state‐of‐the‐science light‐scattering computational capabilities are utilized to simulate the single‐scattering properties across the entire practical size parameter range. The simulated bulk lidar and depolarization ratios of polydisperse ice crystals at wavelength 532 nm are strongly sensitive to the degree of surface roughness. Comparisons of these quantities between the theoretical simulations and counterparts inferred from spaceborne lidar observations for cold cirrus clouds suggest a typical surface‐roughness‐degree range of 0.03–0.15 in the cases of compact hexagonal ice crystals, which is most consistent with direct measurements of scanning electron microscopic images. To properly interpret lidar backscattering observations of ice clouds, it is necessary to account for the degree of surface roughness in light‐scattering computations involving ice crystals.
Plain Language Summary
Lidar (Light Detection and Ranging) instruments on satellites use reflected, or backscattered, laser beams to investigate ice clouds in the atmosphere. However, it has long been a challenge to interpret lidar signals, called backscattering properties, to infer ice cloud characteristics accurately. This study uses theoretical simulations to investigate how small‐scale surface irregularities of ice crystals affect the lidar signals associated with ice clouds. These simulations demonstrate the significant impacts of small‐scale surface irregularities of ice crystals on backscattering. Based on comparisons between the theoretical simulations and satellite lidar observations, it is necessary to assume a moderate degree of small‐scale surface irregularities to explain lidar observations of typical ice clouds.
Key Points
The sensitivity of the backscattering properties to the surface roughness of atmospheric ice crystals is theoretically investigated
The depolarization ratio is substantially sensitive to the degree of surface roughness of ice crystals
Compact hexagonal ice models with degrees of surface roughness ranging 0.03–0.15 reasonably explain the Cloud‐Aerosol Lidar with Orthogonal Polarization backscattering signals
Abstract
A database (TAMUdust2020) of the optical properties of irregular aerosol particles is developed for applications to radiative transfer simulations involving aerosols, particularly dust and ...volcanic ash particles. The particle shape model assumes an ensemble of irregular hexahedral geometries to mimic complex aerosol particle shapes in nature. State-of-the-art light scattering computational capabilities are employed to compute the single-scattering properties of these particles for wide ranges of values of the size parameter, the index of refraction, and the degree of sphericity. The database therefore is useful for various radiative transfer applications over a broad spectral region from ultraviolet to infrared. Overall, agreement between simulations and laboratory/in-situ measurements is achieved for the scattering phase matrix and backscattering of various dust aerosol and volcanic ash particles. Radiative transfer simulations of active and passive spaceborne sensor signals for dust plumes with various aerosol optical depths and the effective particle sizes clearly demonstrate the applicability of the database for aerosol studies. In particular, the present database includes, for the first time, robust backscattering of nonspherical particles spanning the entire range of aerosol particle sizes, which shall be useful to appropriately interpret lidar signals related to the physical properties of aerosol plumes. Furthermore, thermal infrared simulations based on in-situ measured refractive indices of dust aerosol particles manifest the effects of the regional variations of aerosol optical properties. This database includes a user-friendly interface to obtain user-customized aerosol single-scattering properties with respect to spectrally dependent complex refractive index, size, and the degree of sphericity.
Osteosarcoma is the most common primary malignant bone cancer, with high rates of pulmonary metastasis. Osteosarcoma patients with pulmonary metastasis have worse prognosis than those with localized ...disease, leading to dramatically reduced survival rates. Therefore, understanding the biological characteristics of metastatic osteosarcoma and the molecular mechanisms of invasion and metastasis of osteosarcoma cells will lead to the development of innovative therapeutic intervention for advanced osteosarcoma. Here, we identified that osteosarcoma cells commonly exhibit high platelet activation-inducing characteristics, and molecules released from activated platelets promote the invasiveness of osteosarcoma cells. Given that heat-denatured platelet releasate maintained the ability to promote osteosarcoma invasion, we focused on heat-tolerant molecules, such as lipid mediators in the platelet releasate. Osteosarcoma-induced platelet activation leads to abundant lysophosphatidic acid (LPA) release. Exposure to LPA or platelet releasate induced morphological changes and increased invasiveness of osteosarcoma cells. By analyzing publicly available transcriptome datasets and our in-house osteosarcoma patient-derived xenograft tumors, we found that LPA receptor 1 (LPAR1) is notably upregulated in osteosarcoma. LPAR1 gene KO in osteosarcoma cells abolished the platelet-mediated osteosarcoma invasion in vitro and the formation of early pulmonary metastatic foci in experimental pulmonary metastasis models. Of note, the pharmacological inhibition of LPAR1 by the orally available LPAR1 antagonist, ONO-7300243, prevented pulmonary metastasis of osteosarcoma in the mouse models. These results indicate that the LPA-LPAR1 axis is essential for the osteosarcoma invasion and metastasis, and targeting LPAR1 would be a promising therapeutic intervention for advanced osteosarcoma.
A new ice refractive index compilation is reported for a broad spectrum ranging from 0.0443 to 106 μm, focusing on the pronounced temperature‐dependence of ice optical properties in the far‐infrared ...(far‐IR) segment (15–100 μm). A sensitivity study assuming spherical particles shows that selecting ice refractive indices at 12 temperatures and 215 wavelengths in the far‐IR region gives sufficient accuracy in interpolated refractive indices for developing a new ice crystal optical property database. Furthermore, we demonstrate the differences between the bulk single‐scattering properties computed for hexagonal ice particles with this new compilation compared to a previous iteration at three far‐IR wavelengths where substantial differences are noticed between the two ice refractive index compilations. We suggest that our new ice refractive index data set will improve downstream light‐scattering applications for upcoming far‐IR satellite missions and allow robust modeling of outgoing longwave radiation under ice cloud conditions.
Plain Language Summary
An imbalance between absorbed solar energy at ultraviolet (0.01–0.38 μm), visible (0.38–0.75 μm), and near‐infrared (IR) (0.75–2.5 μm) wavelengths and outgoing longwave radiation energy emitted from the Earth at mid‐IR (2.5–15 μm) and far‐IR (15–100 μm) wavelengths leads the surface temperature to change. Solar and mid‐IR energy is well‐observed by satellite sensors. However, it has been challenging to conduct spaceborne radiometric measurements in the far‐IR regime, which accounts for more than half of the OLR in cold areas such as polar regions. This study develops a new compilation of temperature‐dependent ice refractive index for application to the first far‐IR satellite missions extending beyond 25 microns, particularly toward a better understanding of ice clouds. It is shown that the improvements in the ice refractive index have a substantial impact on downstream light‐scattering computation in the far‐IR regime. Furthermore, the present study also explores adequate spectral and temperature resolutions for computing a new ice cloud optical property database to guarantee that the optical property values at other wavelengths and temperatures not included in the direct light‐scattering computations can be accurately obtained through interpolation.
Key Points
A new compilation of ice refractive index covering the entire solar and terrestrial thermal spectrum is presented
This study focuses on the far‐infrared spectrum, which is not well studied but accounts for most terrestrial emissions in cold regions
Implications of improved ice cloud modeling with temperature‐dependent ice refractive indices are discussed
Microorganisms play important roles in the nitrogen cycles of various ecosystems. Research has revealed that a greater diversity of microorganisms is involved in the nitrogen cycle than previously ...understood. It is becoming clear that denitrifying fungi, nitrifying archaea, anammox bacteria, aerobic denitrifying bacteria and heterotrophic nitrifying microorganisms are key players in the nitrogen cycle. Studies have revealed a major contribution by fungi in the production of N
2
O and N
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in grasslands, semiarid regions and forest soils. Some fungi can grow under various O
2
conditions by using three types of energy-yielding metabolism: O
2
respiration, denitrification (nitrite respiration) and ammonia fermentation. The amoA-like gene copies of Crenarchaeota were shown to be more abundant in soils than in autotrophic ammonia-oxidizing bacteria, and the gene was expressed at higher levels in soil to which ammonia was added. There are some contradictory findings, however, regarding archaeal and bacterial nitrification. Anammox bacteria have been shown to be widely distributed and to play an important role in both artificial and natural environments. The contribution of heterotrophic microorganisms to nitrification has been recognized in soil, and the biochemical mechanisms of several bacteria are becoming clear. A wide variety of bacteria have been found to be able to carry out aerobic denitrification and to be distributed across diverse environments. Using molecular biological techniques for soil bacteria, Nitrosospira species of clusters 2, 3 and 4 have been shown to be the dominant group in soils. Genome analyses of autotrophic nitrifying bacteria are providing new insights into their ecology and functions in soils.
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