We introduce a novel analytical expression that allows for fast assessment of mass flow rate of both vertically‐rising and bent‐over volcanic plumes as a function of their height, while first order ...physical insight is maintained. This relationship is compared with a one‐dimensional plume model to demonstrate its flexibility and then validated with observations of the 1980 Mount St. Helens and of the 2010 Eyjafjallajökull eruptions. The influence of wind on the dynamics of volcanic plumes is quantified by a new dimensionless parameter (Π) and it is shown how even vertically‐rising plumes, such as the one associated with the Mount St. Helens 1980 eruption, can be significantly affected by strong wind. Comparison between a one‐dimensional model and the analytical equation gives anR2‐value of 0.88, while existing expressions give negativeR2‐values due to their inability to adapt to different source and atmospheric conditions. Therefore, this new expression has important implications both for current strategies of real‐time forecasting of ash transport in the atmosphere and for the characterization of explosive eruptions based on the study of tephra deposits. In addition, this work provides a framework for the application of more complete three‐dimensional numerical models as it greatly reduces the parameter space that needs to be explored.
Key Points
New analytical expression to derive mass flow rate of volcanic plumes
New dimensionless parameter to assess influence of wind on plume height
Examination of mass flow rates associated with two important eruptions
The size and shape characterization of irregular particles is a key issue in many fields of science, which is often associated with large uncertainties. We assess existing protocols and introduce new ...strategies for the study of size and shape of irregular particles by performing a comprehensive characterization of 127 volcanic clasts with diameters between 155μm and 37mm. Methods include caliper measurements, image analysis, laser scanning and scanning electron microscope micro-computed tomography. Volume, surface area and various shape descriptors including form factors (e.g. flatness, elongation), circularity measures and sphericity are analyzed. First, existing procedures commonly applied by caliper and image analysis to determine 1D (i.e. particle lengths in three dimensions) and 2D variables (e.g. particle projection perimeter and area) have been revised. A new procedure based on particle projection area (PA protocol) for measuring particle lengths in three dimensions is also proposed that is associated with the lowest operator-related errors with respect to existing protocols. In addition, the effect of number of particle projections on the variables obtained through image analysis is investigated. It was found that two to three perpendicular projections can be used to characterize 2D variables with a maximum error of <10%. Second, 1D and 2D variables calculated based on the new PA protocol and image analysis are used to derive shape descriptors and investigate their variability and correlations. Finally, both existing and new empirical correlations for the estimation of 3D particle parameters (i.e. volume, surface area, sphericity) based on 1D and 2D variables are presented and benchmarked. It was found that correlations that are based on 2D variables are associated with the lowest average error (~2.6–4.6%).
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•Characterization of irregular particles in the size range of 155μm to 36mm•A new protocol for the 3D characterization of particle form is presented•Accurate image analysis is achieved by using 2 to 3 particle projections•New correlations are introduced to estimate 3D parameters from 1D and 2D variables•Particle circularity can be used as a proxy for particle sphericity
The Total Grain-Size Distribution (TGSD) of tephra deposits is crucial for hazard assessment and provides fundamental insights into eruption dynamics. It controls both the mass distribution within ...the eruptive plume and the sedimentation processes and can provide essential information on the fragmentation mechanisms. TGSD is typically calculated by integrating deposit grain-size at different locations. The result of such integration is affected not only by the number, but also by the spatial distribution and distance from the vent of the sampling sites. In order to evaluate the reliability of TGSDs, we assessed representative sampling distances for pyroclasts of different sizes through dedicated numerical simulations of tephra dispersal. Results reveal that, depending on wind conditions, a representative grain-size distribution of tephra deposits down to ∼100 μm can be obtained by integrating samples collected at distances from less than one tenth up to a few tens of the column height. The statistical properties of TGSDs representative of a range of eruption styles were calculated by fitting the data with a few general distributions given by the sum of two log-normal distributions (bi-Gaussian in Φ-units), the sum of two Weibull distributions, and a generalized log-logistic distribution for the cumulative number distributions. The main parameters of the bi-lognormal fitting correlate with height of the eruptive columns and magma viscosity, allowing general relationships to be used for estimating TGSD generated in a variety of eruptive styles and for different magma compositions. Fitting results of the cumulative number distribution show two different power law trends for coarse and fine fractions of tephra particles, respectively.
Our results shed light on the complex processes that control the size of particles being injected into the atmosphere during volcanic explosive eruptions and represent the first attempt to assess TGSD on the basis of pivotal physical quantities, such as magma viscosity and plume height. Our empirical method can be used to assess the main features of TGSD necessary for numerical simulations aimed to real-time forecasting and long-term hazard assessment when more accurate field-derived TGSDs are not available.
•We analysed tephra total grain-size distributions derived from field data.•The dataset was described using general statistical distributions.•We found statistical parameters correlate with eruption intensity and magma viscosity.•We propose an empirical method to assess tephra total grain-size distributions.
Total Grain-Size Distribution (TGSD) of tephra deposits is key to the characterization of explosive volcanism, plume-dispersal modeling, and magmatic fragmentation studies. Nonetheless, various ...aspects that includes deposit exposure and data fitting make its determination extremely complex and affect its representativeness. In order to shed some lights on the reliability of derived TGSDs, we examine a large TGSD dataset in combination with a sensitivity analysis of sampling strategies. These analyses are based both on a well-studied tephra deposit and on synthetic deposits associated with a variety of initial eruptive and atmospheric conditions. Results demonstrate that TGSDs can be satisfactorily fitted by four distributions (lognormal, Rosin-Rammler, and power-law based either on the absolute or cumulative number of particles) that capture different distribution features. In particular, the Rosin-Rammler distribution best reproduces both the median and the tails of the TGSDs. The accuracy of reconstructed TGSDs is strongly controlled by the number and distribution of the sampling points. We conclude that TGSDs should be critically assessed based on dedicated sampling strategies and should be fitted by one of the mentioned theoretical distributions depending on the specific study objective (e.g., tephra-deposit characterization, physical description of explosive eruptions, tephra-dispersal modeling).
Accurate forecasting of volcanic particle (tephra) dispersal and fallout requires a reliable estimation of key Eruption Source Parameters (ESPs) such as the Mass Eruption Rate (QM). QM is usually ...estimated from the Top Plume Height (HTP) using empirical and analytical models. For the first time, we combine estimates of HTP and QM derived from the same sensor (radar) with mean wind velocity values (vW) for lava‐fountain fed tephra plumes associated with 32 paroxysms of Mt. Etna (Italy) to develop a new statistical model based on a Markov Chain Monte Carlo approach for model parameter estimation. This model is especially designed for application to radar data to quickly infer QM from observed HTP and vW, and estimate the associated uncertainty. It can be easily applied and adjusted to data retrieved by radars worldwide, improving our capacity to quickly estimate QM and related uncertainties required for the tephra dispersal hazard.
Plain Language Summary
New radar‐based statistical model useful to quickly infer the mass eruption rate, usually the key parameter to initialize the tephra dispersion model, from the volcanic plume height during the eruptions.
Key Points
X‐band radar observations of explosive eruptions can be used to estimate the eruption source parameters and associated uncertainties
Using the Markov Chain Monte Carlo model can be performed the statistical analysis of time series
Statistical parametric model to infer the mass eruption rate from the measured top plume height
Macrophages are a heterogeneous cell population which in response to the cytokine milieu polarize in either classically activated macrophages (M1) or alternatively activated macrophages (M2). This ...plasticity makes macrophages essential in regulating inflammation, immune response and tissue remodeling and a novel therapeutic target in inflammatory diseases such as atherosclerosis. The aim of the study was to describe the transcriptomic profiles of differently polarized human macrophages to generate new hypotheses on the biological function of the different macrophage subtypes.
Polarization of circulating monocytes/macrophages of blood donors was induced in vitro by IFN-γ and LPS (M1), by IL-4 (M2a), and by IL-10 (M2c). Unstimulated cells (RM) served as time controls. Gene expression profile of M1, M2a, M2c and RM was assessed at 6, 12 and 24h after polarization with Whole Human Genome Agilent Microarray technique. When compared to RM, M1 significantly upregulated pathways involved in immunity and inflammation, whereas M2a did the opposite. Conversely, decreased and increased expression of mitochondrial metabolism, consistent with insulin resistant and insulin sensitive patterns, was seen in M1 and M2a, respectively. The time sequence in the expression of some pathways appeared to have some specific bearing on M1 function. Finally, canonical and non-canonical Wnt genes and gene groups, promoting inflammation and tissue remodeling, were upregulated in M2a compared to RM.
Our data in in vitro polarized human macrophages: 1. confirm and extend known inflammatory and anti-inflammatory gene expression patterns; 2. demonstrate changes in mitochondrial metabolism associated to insulin resistance and insulin sensitivity in M1 and M2a, respectively; 3. highlight the potential relevance of gene expression timing in M1 function; 4. unveil enhanced expression of Wnt pathways in M2a suggesting a potential dual (pro-inflammatory and anti-inflammatory) role of M2a in inflammatory diseases.
The collapse of volcanic plumes has significant implications for eruption dynamics and associated hazards. We show how eruptive columns can collapse and generate pyroclastic density currents as a ...result of not only the source conditions, but also of the atmospheric environment. The ratio of the potential energy and the kinetic energy at the source quantified by the Richardson number, and the entrainment efficiency quantified by the radial entrainment coefficient have already been identified as key parameters in controlling the transition between a buoyant and collapsing plume. Here we quantify how this transition is affected by wind using scaling arguments in combination with a one-dimensional plume model. Air entrainment due to wind causes a volcanic plume to lower its density at a faster rate and therefore to favor buoyancy. We identify the conditions when wind entrainment becomes dominant over radial entrainment and quantify the effect of wind on column collapse. These findings are framed into a generalized regime diagram that also describes previous regime diagrams for the specific case of choked flows. Many observations confirm how bent-over plumes typically do not generate significant collapses. A quantitative comparison with the 1996 Ruapehu and the 2010 Eyjafjallajökull eruptions shows that the likelihood of collapse is reduced even at moderate wind speeds relative to the exit velocity at the vent.
•Wind prevents volcanic plumes from collapsing.•New regime diagram for collapse and buoyant plumes.•Comparison of the model predictions with the 1996 Ruapehu and the 2010 Eyjafjallajökull eruptions.
Characterizing the size and settling velocity of pyroclastic fragments injected into the atmosphere during volcanic eruptions (i.e., tephra) is crucial to the forecasting of plume and cloud ...dispersal. Optical disdrometers have been integrated into volcano monitoring networks worldwide in order to best constrain these parameters in real time. Nonetheless, their accuracy during tephra fallout still needs to be assessed. A significant complication is the occurrence of particle aggregates that modify size and velocity distributions of falling tephra. We made the first use of the Thies Clima Laser Precipitation Monitor (LPM) for tephra-fallout detection at Sakurajima volcano (Japan), which is characterized by a lower size detection window with respect to more commonly used disdrometers (e.g., Parsivel
) and can more easily distinguish different falling objects. For the first time, individual particles have been distinguished from most aggregates based on disdrometer data, with the potential to provide useful grain-size information in real time. In case of negligible aggregation, LPM and collected sample-based estimates are in agreement for both grain-size and sedimentation rate. In case of significant aggregation, particle shape analyses and a dedicated drag equation are used to filter out aggregates from LPM data that also provide good agreement with collected tephra samples.
This study examines the sensitivity of atmospheric dispersion model forecasts of volcanic ash clouds to the physical characteristics assigned to the particles. We show that the particle size ...distribution (PSD) used to initialise a dispersion model has a significant impact on the forecast of the mass loading of the ash particles in the atmosphere. This is because the modeled fall velocity of the particles is sensitive to the particle diameter. Forecasts of the long‐range transport of the ash cloud consider particles with diameters between 0.1 μm and 100 μm. The fall velocity of particles with diameter 100 μm is over 5 orders of magnitude greater than a particle with diameter 0.1 μm, and 30 μm particles fall 88% slower and travel up to 5× further than a 100 μm particle. Identifying the PSD of the ash cloud at the source, which is required to initialise a model, is difficult. Further, aggregation processes are currently not explicitly modeled in operational dispersion models due to the high computational costs associated with aggregation schemes. We show that using a modified total grain size distribution (TGSD) that effectively accounts for aggregation processes improves the modeled PSD of the ash cloud and deposits from the eruption of Eyjafjallajökull in 2010. Knowledge of the TGSD of an eruption is therefore critical for reducing uncertainty in quantitative forecasts of ash cloud dispersion. The density and shape assigned to the model particles have a lesser but still significant impact on the calculated fall velocity. Accounting for the density distribution and sphericity of ash from the eruption of Eyjafjallajökull in 2010, modeled particles can travel up to 84% further than particles with default particle characteristics that assume the particles are spherical and have a fixed density.
Key Points
Volcanic Ash Advisory Centres use atmospheric dispersion models
Forecasts are sensitive to the input particle size distribution
The particle density and sphericity assigned have lesser but still significant impacts
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