224 research outputs found

    Quantitative Analysis of Particulate Burden in Lung Tissue

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    Numerous methods have been used in the preparation and analysis of the particulate matter deposited in human lungs. Preparation techniques include those for particle isolation and for in situ analysis. Analytical techniques include bulk and particle-by-particle analysis. In this paper, a general discussion of many of these methods is presented along with examples of how two specific techniques have been used. In one study, individual particles from the lungs of 75 randomly selected autopsy cases were analyzed using an automated scanning electron microscopy (SEM)/ energy dispersive X-ray microanalysis (EDX) system. An average of 613 million particles, of exogenous origin, per gram of dry lung tissue were found, the major classes of particles being silica, talc, aluminum silicates, and rutile. In the second study, lungs from 50 randomly selected autopsy cases were analyzed using gravimetric and X-ray diffraction (XRD) analysis. The median total particulate material was 0.33 grams, for cases in which samples were prepared by high temperature ashing, and 0.41 grams, for those in which nitric acid digestion was used. The median amount of quartz for all cases, was 0.044 grams. Samples of eighteen of the 75 lungs previously analyzed by automated SEM/EDX were also analyzed using gravimetric and XRD analysis. A good correlation was seen between the results of the two procedures (r=0.91 for number of exogenous particles versus grams of particulate matter and r=0.97 for number of silica particles versus amount of quartz)

    Investigating the Accuracy of One-Dimensional Volcanic Plume Models using Laboratory Experiments and Field Data

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    During volcanic eruptions, model predictions of plume height are limited by the accuracy of entrainment coefficients used in many plume models. Typically, two parameters are used, and , which relate the entrained air speed to the jet speed in the axial and cross-flow directions, respectively. To improve estimates of these parameters, wind tunnel experiments have been conducted for a range of cross-wind velocities and turbulence conditions. Measurements are compared directly to computations from the 1-D plume model, Plumeria, in the near-field, bending region of the jet. Entrainment coefficients are determined through regression analysis, demonstrating optimal combinations of effective and values. For turbulent conditions, all wind speeds overlapped at a single combination, = 0.06 and = 0.46, each of which are slightly reduced from standard values. Refined coefficients were used to model plume heights for 20 historical eruptions. Model accuracy improves modestly in most cases, agreeing to within 3 km with observed plume heights. For weak eruptions, uncertainty in field measurements can outweigh the effects of these refinements, illustrating the challenge of applying plume models in practice

    Lung Particulate Burdens of Subjects from the Cincinnati, Ohio Urban Area

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    Because of the relatively small data base existing for lung particulate burdens of subjects with no overt pneumoconioses, the total exogenous lung particulate concentrations of 91 subjects from the Cincinnati, Ohio urban area were determined using an automated scanning electron microscope-energy dispersive x-ray analysis-image analysis system. Four of these subjects were foundry workers and had the highest exogenous particle concentrations seen in the 91 lungs, ranging from 1860 to 2990 x 106 particles per gram of dry lung (ppg). The average exogenous particle concentration for the remaining 87 subjects was 476 ± 380 x 106 ppg with a range of 71 to 1860 x 106 ppg. The median size of the exogenous particles in the 87 lungs was narrow, ranging from 0.37 to 1.02 µm. The geometric mean particle size over all 87 lungs was 0.60 µm with a geometric standard deviation (σg) of 2.35. The total exogenous particle levels were elevated for the male subjects compared to females (p=0.015), and were positively associated with age (p=0. 021). However, no correlation was seen between total particle concentration and race or smoking history

    New techniques for imaging and analyzing lung tissue.

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    The recent technological revolution in the field of imaging techniques has provided pathologists and toxicologists with an expanding repertoire of analytical techniques for studying the interaction between the lung and the various exogenous materials to which it is exposed. Analytical problems requiring elemental sensitivity or specificity beyond the range of that offered by conventional scanning electron microscopy and energy dispersive X-ray analysis are particularly appropriate for the application of these newer techniques. Electron energy loss spectrometry, Auger electron spectroscopy, secondary ion mass spectrometry, and laser microprobe mass analysis each offer unique advantages in this regard, but also possess their own limitations and disadvantages. Diffraction techniques provide crystalline structural information available through no other means. Bulk chemical techniques provide useful cross-checks on the data obtained by microanalytical approaches. It is the purpose of this review to summarize the methodology of these techniques, acknowledge situations in which they have been used in addressing problems in pulmonary toxicology, and comment on the relative advantages and disadvantages of each approach. It is necessary for an investigator to weigh each of these factors when deciding which technique is best suited for any given analytical problem; often it is useful to employ a combination of two or more of the techniques discussed. It is anticipated that there will be increasing utilization of these technologies for problems in pulmonary toxicology in the decades to come

    A One-Dimensional Volcanic Plume Model for Predicting Ash Aggregation

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    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 (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

    Hail formation triggers rapid ash aggregation in volcanic plumes.

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    During explosive eruptions, airborne particles collide and stick together, accelerating the fallout of volcanic ash and climate-forcing aerosols. This aggregation process remains a major source of uncertainty both in ash dispersal forecasting and interpretation of eruptions from the geological record. Here we illuminate the mechanisms and timescales of particle aggregation from a well-characterized 'wet' eruption. The 2009 eruption of Redoubt Volcano, Alaska, incorporated water from the surface (in this case, a glacier), which is a common occurrence during explosive volcanism worldwide. Observations from C-band weather radar, fall deposits and numerical modelling demonstrate that hail-forming processes in the eruption plume triggered aggregation of ∼95% of the fine ash and stripped much of the erupted mass out of the atmosphere within 30 min. Based on these findings, we propose a mechanism of hail-like ash aggregation that contributes to the anomalously rapid fallout of fine ash and occurrence of concentrically layered aggregates in volcanic deposits.AVE acknowledges NSF Postdoctoral Fellowship EAR1250029 and a seed grant from NASA Ames Supercomputing Center. Integrated Data Viewer (IDV) software from UCAR/Unidata was used in the analysis and visualization of the large-eddy simulation. ASTER GDEM is a product of NASA and METI. NCAR Reanalysis data provided by the NOAA/OAR/ESRL Physical Sciences Division, Boulder, Colorado, USA. We acknowledge Victoria University of Wellington, New Zealand, for access to the laser particle size analyzer, and Matt Rogers at University of Alaska, Anchorage for use of the freeze dryer. Rick Hoblitt is thanked for discussions and comments on the manuscript.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/ncomms886

    Seasonal pattern of Echinococcus re-infection in owned dogs in Tibetan communities of Sichuan, China and its implications for control

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    Background Human cystic echinococcosis (CE) and alveolar echinococcosis (AE) are highly endemic in Tibetan communities of Sichuan Province. Previous research in the region indicated that domestic dog was the major source of human infection, and observations indicated that domestic dog could have more access to intermediate hosts of Echinococcus spp.: both domestic livestock (CE) viscera and small mammals (AE), in early winter and again in spring. We hypothesized that there would therefore be a significant increase in the risk of canine infection with Echinococcus spp. in these two seasons and conducted a reinfection study to investigate this further. Methods Faecal samples were collected from owned dogs in seven townships in Ganze Tibetan Autonomous Prefecture (Sichuan Province, China), and Echinococcus spp. infection status was determined using copro-antigen ELISA. Dogs were sampled in April (spring), July (early summer), September/October (autumn/early winter) and December (winter) in 2009; and in April (spring) 2010. Dogs were treated with praziquantel following each of the five sample collections to eliminate any tapeworms. Information on dog sex, age and body weight was also collected. The t-test, Fisher’s exact test, Poisson regression and logistic regression were used to compare means and prevalences, and to identify factors associated with infection status. Results The proportion of female dogs was significantly lower than that of male dogs; female dogs had significantly higher (22.78 %) baseline copro-ELISA prevalence than males (11.88 %). Dog body weight, sex, age, county and previous infection status at any sampling point had no influence on the re-infection prevalence in general. Poisson regression did not found a significant influence on the re-infection prevalence due to different deworming/sampling time spans. Dogs exhibited significantly higher re-infection prevalences in spring and early summer of 2009 and in early winter between September/October and December of 2009, suggesting a higher infection pressure in these seasons comparing with other seasons. Conclusion Following praziquantel treatment, dog body weight, sex, age, county, deworming time span and previous infection status at any sampling point had no influence on the re-infection prevalence in the region in general. The differences between re-infection prevalences were probably due to the seasonality in Echinoccocus spp. infection pressure in the region. Early winter, spring and early summer should be important seasons for optimal dog deworming intervention in these Tibetan communities

    Modelling the transport and deposition of ash following a magnitude 7 eruption: the distal Mazama tephra

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    Volcanic ash transport and dispersion models (VATDMs) are necessary for forecasting tephra dispersal during volcanic eruptions and are a useful tool for estimating the eruption source parameters (ESPs) of prehistoric eruptions. Here we use Ash3D, an Eulerian VATDM, to simulate the tephra deposition from the ~ 7.7 ka climactic eruption of Mount Mazama. We investigate how best to apply a VATDM using the ESPs characteristic of a large magnitude eruption (M ≥ 7). We simplify the approach to focus on the distal deposit as if it were formed by a single phase of Plinian activity. Our results demonstrate that it is possible to use modern wind profiles to simulate the tephra dispersal from a prehistoric eruption; however, this introduces an inherent uncertainty to the subsequent simulations where we explore different ESPs. We show, using the well-documented distal Mazama tephra, that lateral umbrella cloud spreading, rather than advection–diffusion alone, must be included in the VATDM to reproduce the width of the isopachs. In addition, the Ash3D particle size distribution must be modified to simulate the transport and deposition of distal fine-grained (< 125 µm) Mazama ash. With these modifications, the Ash3D simulations reproduce the thickness and grain size of the Mazama tephra deposit. Based on our simulations, however, we conclude that the exact relationship between mass eruption rate and the scale of umbrella cloud spreading remains unresolved. Furthermore, for ground-based grain size distributions to be input directly into Ash3D, further research is required into the atmospheric and particle processes that control the settling behaviour of fine volcanic ash

    Near-real-time volcanic cloud monitoring: insights into global explosive volcanic eruptive activity through analysis of Volcanic Ash Advisories

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    Understanding the location, intensity, and likely duration of volcanic hazards is key to reducing risk from volcanic eruptions. Here, we use a novel near-real-time dataset comprising Volcanic Ash Advisories (VAAs) issued over 10 years to investigate global rates and durations of explosive volcanic activity. The VAAs were collected from the nine Volcanic Ash Advisory Centres (VAACs) worldwide. Information extracted allowed analysis of the frequency and type of explosive behaviour, including analysis of key eruption source parameters (ESPs) such as volcanic cloud height and duration. The results reflect changes in the VAA reporting process, data sources, and volcanic activity through time. The data show an increase in the number of VAAs issued since 2015 that cannot be directly correlated to an increase in volcanic activity. Instead, many represent increased observations, including improved capability to detect low- to mid-level volcanic clouds (FL101–FL200, 3–6 km asl), by higher temporal, spatial, and spectral resolution satellite sensors. Comparison of ESP data extracted from the VAAs with the Mastin et al. (J Volcanol Geotherm Res 186:10–21, 2009a) database shows that traditional assumptions used in the classification of volcanoes could be much simplified for operational use. The analysis highlights the VAA data as an exceptional resource documenting global volcanic activity on timescales that complement more widely used eruption datasets
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