An official website of the United States government
Fecal indicator bacteria currently used for water quality monitoring inadequately represent viral fate in water systems, motivating the development of viral fecal pollution indicators. Molecular viral fecal pollution indicators such as crAssphage and pepper mild mottle virus (PMMoV) have emerged as leading viral fecal pollution indicator candidates due to ease and speed of measurement and target specificity. Elucidating the fate of molecular viral fecal indicators in water systems is necessary to facilitate their development, broader adoption, and ultimately their association with infectious risk. A significant mechanism controlling the behavior of viral indicators in environmental waters is association with particles, as this would dictate removal via settling and transport characteristics. In this study, we investigated the particle associations of six molecular fecal pollution targets (crAssphage, PMMoV, adenovirus, human polyomavirus, norovirus, HF183/BacR287) in wastewater using a cascade filtration approach. Four different filters were employed representing large settleable particles (180 μm), larger (20 μm) and smaller suspended particles (0.45 μm), and non-settleable particles (0.03 μm). All molecular targets were detected on all particle size fractions; however, all targets had their highest concentrations on the 0.45 μm (percent contribution ranging from 40% to 80.5%) and 20 μm (percent contribution ranging from 3.9% to 39.4%) filters. The association of viral fecal pollution targets with suspended particles suggests that particle association will dictate transport in environmental waters and that sample concentration approaches based upon particle collection will be effective for these targets.
more »
« less
Experimental Measurement of Enhanced and Hindered Particle Settling in Turbulent Gas‐Particle Suspensions, and Geophysical Implications
Abstract The dynamics of geophysical dilute turbulent gas‐particles mixtures depends to a large extent on particle concentration, which in turn depends predominantly on the particle settling velocity. We experimentally investigate air‐particle mixtures contained in a vertical pipe in which the velocity of an ascending air flux matches the settling velocity of glass particles. To obtain local particle concentrations in these mixtures, we use acoustic probing and air pressure measurements and show that these independent techniques yield similar results for a range of particle sizes and particle concentrations. Moreover, we find that in suspensions of small particles (78 μm) the settling velocity increases with the local particle concentration due to the formation of particle clusters. These clusters settle with a velocity that is four times faster than the terminal settling velocity of single particles, and they double settling speeds of the suspensions. In contrast, in suspensions of larger particles (467 μm) the settling velocity decreases with increasing particle concentration. Although particle clusters are still present in this case, the settling velocity is decreased by 30%, which is captured by a hindered settling model. These results suggest an interplay between hindered settling and cluster‐induced enhanced settling, which in our experiments occur respectively at Stokes number O(100) and O(1). We discuss implications for volcanic plumes and pyroclastic currents. Our study suggests that clustering and related enhanced or hindered particle settling velocities should be considered in models of volcanic phenomena and that drag law corrections are needed for reliable predictions and hazard assessment.
more »
« less
- Award ID(s):
- 2042173
- PAR ID:
- 10399795
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Solid Earth
- Volume:
- 128
- Issue:
- 3
- ISSN:
- 2169-9313
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Flowing granular materials segregate due to differences in particle size (driven by percolation) and density (driven by buoyancy). Modelling the segregation of mixtures of large/heavy particles and small/light particles is challenging due to the opposing effects of the two segregation mechanisms. Using discrete element method (DEM) simulations of combined size and density segregation we show that the segregation velocity is well described by a model that depends linearly on the local shear rate and quadratically on the species concentration for free surface flows. Concentration profiles predicted by incorporating this segregation velocity model into a continuum advection–diffusion–segregation transport model match DEM simulation results well for a wide range of particle size and density ratios. Most surprisingly, the DEM simulations and the segregation velocity model both show that the segregation direction for a range of size and density ratios depends on the local species concentration. This leads to a methodology to determine the combination of particle size ratio, density ratio and particle concentration for which a bidisperse mixture will not segregate.more » « less
-
null (Ed.)The effect of turbulence on snow precipitation is not incorporated into present weather forecasting models. Here we show evidence that turbulence is in fact a key influence on both fall speed and spatial distribution of settling snow. We consider three snowfall events under vastly different levels of atmospheric turbulence. We characterize the size and morphology of the snow particles, and we simultaneously image their velocity, acceleration and relative concentration over vertical planes approximately $$30\ \textrm {m}^2$$ in area. We find that turbulence-driven settling enhancement explains otherwise contradictory trends between the particle size and velocity. The estimates of the Stokes number and the correlation between vertical velocity and local concentration are consistent with the view that the enhanced settling is rooted in the preferential sweeping mechanism. When the snow vertical velocity is large compared to the characteristic turbulence velocity, the crossing trajectories effect results in strong accelerations. When the conditions of preferential sweeping are met, the concentration field is highly non-uniform and clustering appears over a wide range of scales. These clusters, identified for the first time in a naturally occurring flow, display the signature features seen in canonical settings: power-law size distribution, fractal-like shape, vertical elongation and large fall speed that increases with the cluster size. These findings demonstrate that the fundamental phenomenology of particle-laden turbulence can be leveraged towards a better predictive understanding of snow precipitation and ground snow accumulation. They also demonstrate how environmental flows can be used to investigate dispersed multiphase flows at Reynolds numbers not accessible in laboratory experiments or numerical simulations.more » « less
-
Abstract During explosive volcanic eruptions, volcanic ash is ejected into the atmosphere, impacting aircraft safety and downwind communities. These volcanic clouds tend to be dominated by fine ash (<63 μm in diameter), permitting transport over hundreds to thousands of kilometers. However, field observations show that much of this fine ash aggregates into clusters or pellets with faster settling velocities than individual particles. Models of ash transport and deposition require an understanding of aggregation processes, which depend on factors like moisture content and local particle collision rates. In this study, we develop a Plume Model for Aggregate Prediction, a one‐dimensional (1D) volcanic plume model that predicts the plume rise height, concentration of water phases, and size distribution of resulting ash aggregates from a set of eruption source parameters. The plume model uses a control volume approach to solve mass, momentum, and energy equations along the direction of the plume axis. The aggregation equation is solved using a fixed pivot technique and incorporates a sticking efficiency model developed from analog laboratory experiments of particle aggregation within a novel turbulence tower. When applied to the 2009 eruption of Redoubt Volcano, Alaska, the 1D model predicts that the majority of the plume is over‐saturated with water, leading to a high rate of aggregation. Although the mean grain size of the computed Redoubt aggregates is larger than the measured deposits, with a peak at 1 mm rather than 500 μm, the present results provide a quantitative estimate for the magnitude of aggregation in an eruption.more » « less
-
Capillary suspensions are three-phase mixtures containing a solid particulate phase, a continuous liquid phase, and a second immiscible liquid forming capillary bridges between particles. Capillary suspensions are encountered in a wide array of applications including 3D printing, porous materials, and food formulations, but despite recent progress, the micromechanics of particle clusters in flow is not fully understood. In this work, we study the dynamics of meniscus-bound particle clusters in planar extensional flow using a Stokes trap, which is an automated flow control technique that allows for precise manipulation of freely suspended particles or particle clusters in flow. Focusing on the case of a two-particle doublet, we use a combination of experiments and analytical modeling to understand how particle clusters rearrange, deform, and ultimately break up in extensional flow. The time required for cluster breakup is quantified as a function of capillary number Ca and meniscus volume V. Importantly, a critical capillary number Cacrit for cluster breakup is determined using a combination of experiments and modeling. Cluster relaxation experiments are also performed by deforming particle clusters in flow, followed by flow cessation prior to breakup and observing cluster relaxation dynamics under zero-flow conditions. In all cases, experiments are complemented by an analytical model that accounts for capillary forces, lubrication forces, hydrodynamic drag forces, and hydrodynamic interactions acting on the particles. Results from the analytical models are found to be in good agreement with experiments. Overall, this work provides a new quantitative understanding of the deformation dynamics of capillary clusters in extensional flow.more » « less
