Determination of PCDDs and PCDFs in PCB oil from a hazardous waste site

This paper describes the analysis of hazardous waste oil samples with procedures that were developed primarily to clean up and analyze biological samples. Details of the cleanup procedure and the results from the analysis of several waste PCB oil samples are presented.     

Release of phagocytosis-stimulating factor(s) by morula cells in a colonial ascidian

In vitro yeast phagocytosis by haemocytes of the compound ascidian Botryllus schlosseri was studied, with particular attention to interactions among different immunocyte types. It is demonstrated that the supernatant from haemocyte cultures matched with yeast cells contains factor(s) able to enhance yeast ingestion by Botryllus phagocytes. The increase in phagocytosis is not the consequence of yeast opsonisation, as the phagocytic index does not significantly increase when yeast cells, previously incubated in the culture media, are washed and re-suspended in filtered sea water. When haemocytes were fractionated by density gradient centrifugation and each band was incubated with yeast, the ability to stimulate phagocytosis was found in the supernatants from haemocyte cultures of fractions rich in morula cells (MC). Previous studies have demonstrated that MC express molecules recognised by anti-cytokine antibodies, as a consequence of the recognition of foreign molecules or cells. Our results indicate that molecules immunoreactive with anti-cytokine antibodies are required for modulating phagocyte activity, as the above-reported enhancing effect is completely absent in the presence of anti-IL-1-α and anti-TNF-α, but not of anti-rabbit-IgG antibodies, and they also highlight the presence of ‘cross-talk‘ between MC and phagocytes. A new scenario is therefore sketched, in which MC actively recognise non-self molecular patterns and, upon this recognition, release humoural factor(s) recognised by phagocytes, which modulate phagocytosis.     

用扫描电镜分析表征大气气溶胶单颗粒

1　IntroductionAtmosphericaerosolsarecomplexmixture,originatedfromavarietyofsources.Mostoftheanalyticaltechniquesusedforitscharacterizationarebulkmethodsthatgenerateonesetofdatapersample,describingtheoverallcompositionofthesample .Toworkoutusefulinformationonpollu tionsources,itrequiresdataofagreatnumberofsamplesandmultivariatedataanalysismethodsusuallyareneeded .Ontheotherhand ,scanningelectronmicroscope energydispersiveX rayanaly sissystem (SEM EDX)isabletoprovideanalyticaldataforeachsing…     

Two-phase modeling of sediment clouds

A sediment cloud release in stagnant ambient fluid occurs in many engineering applications. Examples include land reclamation and disposal of dredged materials. The detailed modeling of the distinct characteristics of both the solid and fluid phases of the sediment cloud is hitherto unavailable in the literature despite their importance in practice. In this paper, the two-phase mixing characteristics of the sediment cloud are investigated both experimentally and theoretically. Experiments were carried out to measure the transient depth penetration and the lateral spread of the sediment cloud and its entrained fluid using the laser induced fluorescence technique, with a range of particle sizes frequently encountered in the field (modeled at laboratory scale). A two-phase model of the sediment cloud that provides detailed predictions of the mixing characteristics of the individual phases is also proposed. The entrained fluid characteristics are solved by an integral model accounting for the buoyancy loss (due to particle separation) in each time step. The flow field induced by the sediment cloud is approximated by a Hill’s spherical vortex centered at the centroid and with the size of the entrained fluid. The particle equation of motion under the effect of the induced flow governs each computational particle. A random walk model using the hydrodynamic diffusion coefficient is used to account for the random fluctuation of particles in the dispersive regime. Overall, the model predictions of the two-phase mixing characteristics are in good agreement with the experimental data for a wide range of release conditions.     

Field‐Scale Application of Three Types of Neural Networks to Predict Ground‐Water Levels1

Abstract: In this paper, a field‐scale applicability of three forms of artificial neural network algorithms in forecasting short‐term ground‐water levels at specific control points is presented. These algorithms are the feed‐forward back propagation (FFBP), radial basis networks (RBN), and generalized regression networks (GRN). Ground‐water level predictions from these algorithms are in turn to be used in an Optimized Regional Operations Plan that prescribes scheduled wellfield production for the coming four weeks. These models are up against each other for their accuracy of ground‐water level predictions on lead times ranging from a week to four weeks, ease of implementation, and execution times (mainly training time). In total, 208 networks of each of the three algorithms were developed for the study. It is shown that although learning algorithms have emerged as a viable solution at field scale much larger than previously studied, no single algorithm performs consistently better than others on all the criteria. On average, FFBP networks are 20 and 26%, respectively, more accurate than RBN and GRN in forecasting one week ahead water levels and this advantage drops to 5 and 9% accuracy in forecasting four weeks ahead water levels, whereas GRN posted a training time that is only 5% of the training time taken by that of FFBP networks. This may suggest that in field‐scale applications one may have to trade between the type of algorithm to be used and the degree to which a given objective is honored.     

Spatiotemporal analysis of traffic emissions in over 5000 municipal districts in Brazil

Exposure to traffic emission is harmful to human health. Emission inventories are essential to public health policies aiming at protecting human health, especially in areas with incomplete or nonexistent air pollution monitoring networks. In Brazil, for example, only 1.7% of municipal districts have a monitoring network, and only a few studies have reported data on vehicle emission inventories. No studies have presented emission inventories by municipality. In this study, we predicted vehicular emissions for 5570 municipal districts in Brazil during the period 2001–2012. We used a top-down method to estimate emissions. Carbon dioxide (CO₂) is the pollutant with the highest emissions, with approximately 190 million tons per year during the period 2001–2012). For the other traffic-related pollutants, we predicted annual emissions of 1.5 million tons for carbon monoxide (CO), 1.2 million tons of nitrogen oxides (NO_x), 209,000 tons of nonmethane hydrocarbons (NMHC), 58,000 tons of particulate matter (PM), and 42,000 tons for methane (CH₄). From 2001 to 2012, CO, NMHC, and PM emissions decreased by 41, 33, and 47%, respectively, whereas those CH₄, NO_x, and CO₂ increased by 2, 4, and 84%, respectively. We estimated uncertainties in our study and found that NO_x was the pollutant with the lowest percentage difference, 8%, and NMHC with the highest one, 30%. For CO, CH₄, CO₂, and PM, the values were 22, 14, 21, and 20%, respectively. Finally, we found that during 2001 and 2012 emissions increased in the Northwest and Northeast. In contrast, pollutant emissions, except for CO₂, decreased in the Southeast, South, and part of Midwest. Our predictions can be critical to efforts developing cost-effective public policies tailored to individual municipal districts in Brazil.

Implications: Emission inventories may be an alternative approach to provide data for air quality forecasting in areas where air quality data are not available. This approach can be an effective tool in developing spatially resolved emission inventories.     

Indoor/ambient residential air toxics results in rural western Montana

Indoor and ambient concentrations of 21 volatile organic compounds (including 14 hazardous air pollutants) were measured in the homes of nearly 80 western Montana (Missoula) high school students as part of the 'Air Toxics Under the Big Sky' program during the 2004/2005 and 2005/2006 school years. Target analytes were measured using low flow air sampling pumps and sorbent tubes, with analysis of the exposed samples by thermal desorption/gas chromatography/mass spectrometry (TD/GC/MS). The results reported here present the findings of the first indoor/ambient air toxics monitoring program conducted in a semi-rural valley location located in the Northern Rocky Mountain/Western Montana region. Of all of the air toxics quantified in this study, toluene was found to be the most abundant compound in both the indoor and ambient environments during each of the two school years. Indoor log-transformed mean concentrations were found to be higher when compared with ambient log-transformed mean concentrations at P < 0.001 for the majority of the compounds, supporting the results of previous studies conducted in urban areas. For the air toxics consistently measured throughout this program, concentrations were approximately six times higher inside the student's homes compared to those simultaneously measured directly outside their homes. For the majority of the compounds, there were no significant correlations between indoor and ambient concentrations.     

Temporal Trends of Young-of-Year Fishes in Lake Erie and Comparison of Diel Sampling Periods

We explored temporal trends of young-of-year (YOY) fishes caught in bottom trawl hauls at an established offshore monitoring site in Lake Erie in fall during 1961–2001. Sampling was conducted during morning, afternoon, and night in each year. Catches per hour (CPH) of alewife (Alosa pseudoharengus) YOY were relatively low and exhibited no temporal trend. This result was consistent with the species’ intolerance to Lake Erie’s adverse winter water temperatures. Gizzard shad (Dorosoma cepedianum) YOY decreased sharply after 1991, which was consistent with recent oligotrophication of the lake. Following the establishment in 1979 and rapid increase of white perch (Morone americana) YOY, white bass (Morone chrysops) and freshwater drum (Aplodinotus grunniens) YOY decreased. Trout-perch (Percopsis omiscomaycus) YOY decreased during 1986–1991, but recovered to previous levels during 1991–2001. The recovery coincided with the resurgence of mayflies (Ephemoptera) in the lake. CPH of spottail shiner (Notropis hudsonius) and emerald shiner (N. atherinoides) YOY exhibited no temporal trend between 1961 and the late 1970s to early 1980s. CPH of yellow perch (Perca flavescens) YOY decreased during 1961–1988, and walleye (Sander vitreum) YOY increased overall during the time series. These observations were consistent with published studies of adults in the region. CPH of 4 of the 10 species of YOY considered were greatest during night. CPH for walleye YOY was higher in the morning than in the afternoon, but there was no significant difference between night and morning abundances. The results suggest that (1) CPH of YOY fishes may be a useful monitoring tool for Lake Erie, and (2) offshore monitoring programs that do not include night sampling periods may underestimate recruitment for several common species.     

Analysis of two-state multivariate phenotypic change in ecological studies

Analyses of two-state phenotypic change are common in ecological research. Some examples include phenotypic changes due to phenotypic plasticity between two environments, changes due to predator/non-predator character shifts, character displacement via competitive interactions, and patterns of sexual dimorphism. However, methods for analyzing phenotypic change for multivariate data have not been rigorously developed. Here we outline a method for testing vectors of phenotypic change in terms of two important attributes: the magnitude of change (vector length) and the direction of change described by trait covariation (angular difference between vectors). We describe a permutation procedure for testing these attributes, which allows non-targeted sources of variation to be held constant. We provide examples that illustrate the importance of considering vector attributes of phenotypic change in biological studies, and we demonstrate how greater inference can be made than by evaluating variance components with MANOVA alone. Finally, we consider how our method may be extended to more complex data.