Controls on the size distributions of shallow landslides

Rainfall-triggered shallow landslides are destructive hazards and play an important role in landscape processes. A theory explaining the size distributions of such features remains elusive. Prior work connects size distributions to topography, but field-mapped inventories reveal pronounced similarities in the form, mode, and spread of distributions from diverse landscapes. We analyze nearly identical distributions occurring in the Oregon Coast Range and the English Lake District, two regions of strikingly different topography, lithology, and vegetation. Similarity in minimum sizes at these sites is partly explained by theory that accounts for the interplay of mechanical soil strength controls resisting failure. Maximum sizes, however, are not explained by current theory. We develop a generalized framework to account for the entire size distribution by unifying a mechanistic slope stability model with a flexible spatial-statistical description for the variability of hillslope strength. Using hillslope-scale numerical experiments, we find that landslides can occur not only in individual low strength areas but also across multiple smaller patches that coalesce. We show that reproducing observed size distributions requires spatial strength variations to be strongly localized, of large amplitude, and a consequence of multiple interacting factors. Such constraints can act together with the mechanical determinants of landslide initiation to produce size distributions of broadly similar character in widely different landscapes, as found in our examples. We propose that size distributions reflect the systematic scale dependence of the spatially averaged strength. Our results highlight the critical need to constrain the form, amplitude, and wavelength of spatial variability in material strength properties of hillslopes.

Aerosol formation due to a dental procedure: insights leading to the transmission of diseases to the environment

As a result of the outbreak and diffusion of SARS-CoV-2, there has been a directive to advance medical working conditions. In dentistry, airborne particles are produced through aerosolization facilitated by dental instruments. To develop methods for reducing the risks of infection in a confined environment, understanding the nature and dynamics of these droplets is imperative and timely. This study provides the first evidence of aerosol droplet formation from an ultrasonic scalar under simulated oral conditions. State-of-the-art optical flow tracking velocimetry and shadowgraphy measurements are employed to quantitatively measure the flow velocity, trajectories and size distribution of droplets produced during a dental scaling process. The droplet sizes are found to vary from 5 µm to 300 µm; these correspond to droplet nuclei that could carry viruses. The droplet velocities also vary between 1.3 m s-1 and 2.6 m s-1. These observations confirm the critical role of aerosols in the transmission of disease during dental procedures, and provide invaluable knowledge for developing protocols and procedures to ensure the safety of both dentists and patients.

[Characterization and Size Distribution of Carbonaceous Aerosols at Mountain Dinghu]

To understand the characterization and sources of carbonaceous aerosols at Mountain Dinghu, organic carbon (OC) and elemental carbon (EC) in size-resolved aerosol samples were measured at a regional background site in South China using a DRI Model 2001A analyzer. The average mass concentrations of organic carbon (OC) are (5.6±2.0) μg ·m^-3 in PM_1.1, (7.3±2.4) μg ·m^-3 in PM_2.1, and (12.8±4.0) μg ·m^-3 in PM_9.0; the average mass concentrations of elemental carbon (EC) are (2.3±1.4) μg ·m^-3in PM_1.1, (2.7±1.6) μg ·m^-3 in PM_2.1, and (3.4±1.7) μg ·m^-3 in PM_9.0. OC concentrations in PM_1.1 and PM_2.1 account for 43.8% and 57.0% of OC in PM_9.0, and EC concentrations in PM_1.1 and PM_2.1 account for 67.6% and 79.4%, respectively. OC and EC are enriched with fine particles. In PM_1.1 and PM_2.1, the highest concentrations of OC and EC are measured in autumn, and the lowest concentration of OC is measured in winter and EC in summer. In PM_9.0, the highest OC concentration is measured in summer. Carbonaceous aerosols are mainly composed of OC2, EC1, OC3, and OC4. In summer, the concentration of OC3 is higher than that of EC1, suggesting that biogenic sources are dominant during summer. The concentration of EC1 in winter is the highest, indicating that the impacts of motor vehicle emissions are prominent in the local area during winter. OC and EC both show bimodal distributions in four seasons, with peaks in the size ranges of 0.43-0.65 μm for fine particles and 3.3-5.8 μm for coarse particles. In PM_1.1 and PM_2.1, the sources of OC are mainly primary emissions. In PM_2.1, the highest concentration of SOC is measured in spring at (3.0±1.4) μg ·m^-3 and the lowest in winter at (1.3±1.4) μg ·m^-3, indicating that the secondary aerosol formation is significant in spring. At the Mountain Dinghu background site, OC is mainly from coal combustion and motor vehicle emissions for fine particles and from biogenic sources for coarse particles. EC is mainly from coal combustion, motor vehicle emissions, and dust.

Single-Particle Tracking for Understanding Polydisperse Nanoparticle Dispersions

Colloidal dispersions of nanomaterials are often polydisperse in size, significantly complicating their characterization. This is particularly true for materials early in their historical development due to synthetic control, dispersion efficiency, and instability during storage. Because a wide range of system properties and technological applications depend on particle dimensions, it remains an important problem in nanotechnology to identify a method for the routine characterization of polydispersity in nanoparticle samples, especially changes over time. Commonly employed methods such as dynamic light scattering or analytical ultracentrifugation (AUC) accurately estimate only the first moment of the distribution or are not routine. In this work, the use of single-particle tracking (SPT) to probe size distributions of common nanoparticle dispersions, including polystyrene nanoparticles, single-walled carbon nanotubes, graphene oxide, chitosan-tripolyphosphate, acrylate, hexagonal boron nitride, and poly(lactic-co-glycolic acid), is proposed and explored. The analysis of particle tracks is conducted using a newly developed Bayesian algorithm that is called Maximum A posteriori Nanoparticle Tracking Analysis. By combining SPT and AUC techniques, it is shown that it is possible to independently estimate the mean aspect ratio of anisotropic particles, an important characterization property. It is concluded that SPT provides a facile, rapid analytical method for routine nanomaterials characterization.

Aerosols and criteria gases in an underground mine that uses FAME biodiesel blends

The contribution of heavy-duty haulage trucks to the concentrations of aerosols and criteria gases in underground mine air and the physical properties of those aerosols were assessed for three fuel blends made with fatty acid methyl esters biodiesel and petroleum-based ultra-low-sulfur diesel (ULSD). The contributions of blends with 20, 50, and 57% of biodiesel as well as neat ULSD were assessed using a 30-ton truck operated over a simulated production cycle in an isolated zone of an operating underground metal mine. When fueled with the B20 (blend of biodiesel with ULSD with 20% of biodiesel content), B50 (blend of biodiesel with ULSD with 50% of biodiesel content), and B57 (blend of biodiesel with ULSD with 57% of biodiesel content) blends in place of ULSD, the truck's contribution to mass concentrations of elemental and total carbon was reduced by 20, 50, and 61%, respectively. Size distribution measurements showed that the aerosols produced by the engine fueled with these blends were characterized by smaller median electrical mobility diameter and lower peak concentrations than the aerosols produced by the same engine fueled with ULSD. The use of the blends resulted in number concentrations of aerosols that were 13-29% lower than those when ULSD was used. Depending on the content of biodiesel in the blends, the average reductions in the surface area concentrations of aerosol which could be deposited in the alveolar region of the lung (as measured by a nanoparticle surface area monitor) ranged between 6 and 37%. The use of blends also resulted in slight but measurable reductions in CO emissions, as well as an increase in NOX emissions. All of the above changes in concentrations and physical properties were found to be correlated with the proportion of biodiesel in the blends.

Ecological emergence of thermal clines in body size

The unprecedented rate of global warming requires a better understanding of how ecosystems will respond. Organisms often have smaller body sizes under warmer climates (Bergmann's rule and the temperature-size rule), and body size is a major determinant of life histories, demography, population size, nutrient turnover rate, and food-web structure. Therefore, by altering body sizes in whole communities, current warming can potentially disrupt ecosystem function and services. However, the underlying drivers of warming-induced body downsizing remain far from clear. Here, we show that thermal clines in body size are predicted from universal laws of ecology and metabolism, so that size-dependent selection from competition (both intra and interspecific) and predation favors smaller individuals under warmer conditions. We validate this prediction using 4.1 × 10(6) individual body size measurements from French river fish spanning 29 years and 52 species. Our results suggest that warming-induced body downsizing is an emergent property of size-structured food webs, and highlight the need to consider trophic interactions when predicting biosphere reorganizations under global warming.

A new adaptive grid-size algorithm for the simulation of sedimentation velocity profiles in analytical ultracentrifugation

Analytical ultracentrifugation allows one to measure in real-time the concentration gradients arising from the application of a centrifugal force to macromolecular mixtures in solution. In the last decade, the ability to efficiently solve the partial differential equation governing the ultracentrifugal sedimentation and diffusion process, the Lamm equation, has spawned significant progress in the application of sedimentation velocity analytical ultracentrifugation for the study of biological macromolecules, for example, the characterization of protein oligomeric states and the study of reversible multi-protein complexes in solution. The present work describes a numerical algorithm that can provide an improvement in accuracy or efficiency over existing algorithms by more than one order of magnitude, and thereby greatly facilitate the practical application of sedimentation velocity analysis, in particular, for the study of multi-component macromolecular mixtures. It is implemented in the public domain software SEDFIT for the analysis of experimental data.