A comparison of methods and materials for the analysis of leaded wipes

The purposes of this study are: (1) to determine whether proficiency analytical test (PAT) materials from the American Industrial Hygiene Association can be used to provide quality data for portable X-ray fluorescence analysis (XRF) of lead in dust wipe surface samples; (2) to provide data to determine whether the on-site analysis of field dust wipe samples by XRF and the laboratory method of inductively coupled plasma emission analysis (ICP) are comparable; and (3) to determine if differences exist between different wipe materials. Several wipes meet the ASTM E1792 performance requirements of lead background level less than 5 microg per wipe, be only one layer thick, yield recovery rates of 80- 120% from spiked samples, remain damp throughout the sampling procedure, and do not contain aloe. The wipes used in this study were Pace Wipes, which are used for the PAT materials, and, for the field samples, Palintest Wipes, which were supplied by the instrument manufacturer, and Ghost Wipes, which are popular because they digest in hot, concentrated acid, so that chemical analysis is simplified. Twenty PAT wipe samples were obtained from four different proficiency test rounds. Surface wipe samples were taken at three different locations representing different industry types. All samples were analyzed using a portable XRF spectrometer and by ICP. Strong linear relationships were found for the analysis of wipe samples by ICP and by portable XRF. For the PAT samples, the results from the ICP and XRF analysis were not statistically equivalent, which indicates a bias in the ICP analysis. The bias was not excessive, since all ICP analyses fell within the acceptable range for the proficiency samples. The good correlation between the proficiency sample reference values and the XRF determinations is not surprising considering similar proficiency samples were used to calibrate the instrument response. Users of this portable XRF analyzer could enroll in the proficiency test program as part of their quality assurance program. For field samples, the relationship was strongest for Palintest wipes, and the values found for all three industries could be combined. However, the results from the ICP and XRF analysis were not statistically equivalent using the correction factor in the calculation algorithm as supplied with the instrument, and a new coefficient was derived. The mean relative error for the XRF analysis versus the ICP analysis was greater than 25%, such that the method falls within the realm of screening procedures. For Ghost Wipe samples, the precision was different for different industries, and the results could not be pooled. Differences between the two wipe materials may be related to the number of folds required for analysis.     

Sampling over time: developing a cost effective and precise exposure assessment program

Studies requiring ambient exposure assessments invariably ask: How often should measurements be taken? Answer to such questions is dictated by budgetary considerations as well as spatial and temporal variability in the data. For example, do we obtain measurements during all seasons, all months within seasons, weeks within months and days within weeks? On one hand, we can obtain a one-time snapshot sample and regard it as representing the "true" mean exposure. On the other hand, we may obtain a large number of measurements over time and then average these in order to represent this "true" mean exposure. The former estimate is the least expensive but may also be the least precise while the latter, may be very precise but prohibitively costly. In this paper, we demonstrate how a pilot study can be undertaken with a potentially promising and feasible sampling plan for the full-scale study. By applying the statistical methodology of variance component analysis (VCA) to the pilot study data and exploiting mathematical relationship between the variance of the overall mean exposure and posited variance components, we can develop a sampling design with decreased sampling costs and/or increased precision of the mean exposure. Our approach was applied to determine sampling design choices for an on-going study that aimed at assessing ambient particulate matter exposure. We conclude that a pilot study followed by the VCA analysis may often lead to sampling design choices that offer considerable cost savings and, at the same time, promise to provide relatively precise estimates of the mean exposure for the subsequent full-scale study.     

Can Nutrient Spiralling be Used to Detect Seasonal Nutrient Uptake in a Forested Stream?

Nutrient spiralling measurements were conducted in Lyrebird Creek, a forested stream in the Dandenong Ranges, Victoria, Australia. Spiralling indices from several nutrient (, ) enrichment experiments were correlated with seasonal variation in factors thought to control nutrient uptake, i.e., temperature, light and algal biomass. It was hypothesized that nutrient uptake would be higher in summer as increased temperatures would promote both biotic and abiotic processes and higher light levels in summer would stimulate photosynthesis. However, results did not support this hypothesis. Uptake length for and and uptake velocity were not correlated with chlorophyll-a, light or temperature (r ² < 0.30, P > 0.1) despite the seasonality of these biophysical factors (r ² > 0.42, P < 0.02). Lyrebird Creek might had no seasonal trend in nutrient uptake and/or nutrient spiraling measurements only appears suitable for contrasting streams with large differences in biophysical factors that supports biotic and abiotic nutrient processing. In addition, small errors in measuring a nutrient concentration can result in a large range in the estimated S _w and increased difficulty in determining significant differences in nutrient spiralling indices.     

An approach for measuring methane emissions from whole farms

Estimates of enteric methane (CH4) emissions from ruminants are typically measured by confining animals in large chambers, using head hoods or masks, or by a ratiometric technique involving sampling respired air of the animal. These techniques are not appropriate to evaluate large-scale farm emissions and the variability between farms that may be partly attributed to different farm management. This study describes the application of an inverse-dispersion technique to calculate farm emissions in a controlled tracer-release experiment. Our study was conducted at a commercial dairy farm in southern Alberta, Canada (total of 321 cattle, including 152 lactating dairy cows). Sulfur hexafluoride (SF6) and CH4 were released from 10 outlet locations (barn and open pens) using mass-flow controllers. A Lagrangian stochastic (LS) dispersion model was then used to infer farm emissions from downwind gas concentrations. Concentrations of SF6 and CH4 were measured by gas chromatography analysis and open path lasers, respectively. Wind statistics were measured with a three-dimensional sonic anemometer. Comparing the inferred emissions with the known release rate showed we recovered 86% of the released CH4 and 100% of the released SF6. The location of the concentration observations downwind of the farm was critically important to the success of this technique.     

Local varieties of cassava: conservation,cultivation and use in Uganda

The study explored the theory that on-farm conservation of cassava germplasm is influenced by farmers’ traditional and cultural preferences of particular varieties. Traditional knowledge practices that are used for on-farm conservation of cassava germplasm as well as cassava attributes for selection were assessed. The findings obtained from the study indicated that farmers use traditional knowledge to select and preserve cassava germplasm for future use. It was also clear that farmers have their preferences such as culinary attributes, storability in the ground, early maturity and cooking quality to mention but a few that influence the decisions taken to retain or abandon cultivation of varieties. Therefore, by planting varieties in multiples plots, replanting immediately after harvesting, sharing with others in the community and planting disease-free materials, farmers ensure that they preserve varieties of interest for decades. The information generated during this study could inform development policies tailored toward ensuring sustainable on-farm conservation of cassava genetic resources.     

Bivalve mollusks in metal pollution studies: From bioaccumulation to biomonitoring

Contemporary environmental challenges have emphasized the need to critically assess the use of bivalve mollusks in chemical monitoring (identification and quantification of pollutants) and biomonitoring (estimation of environmental quality). Many authors, however, have considered these approaches within a single context, i.e., as a means of chemical (e.g. metal) monitoring. Bivalves are able to accumulate substantial amounts of metals from ambient water, but evidence for the drastic effects of accumulated metals (e.g. as a TBT-induced shell deformation and imposex) on the health of bivalves has not been documented. Metal bioaccumulation is a key tool in biomonitoring; bioavailability, bioaccumulation, and toxicity of various metals in relation to bivalves are described in some detail including the development of biodynamic metal bioaccumulation model. Measuring metal in the whole-body or the tissue of bivalves themselves does not accurately represent true contamination levels in the environment; these data are critical for our understanding of contaminant trends at sampling sites. Only rarely has metal bioaccumulation been considered in combination with data on metal concentrations in parts of the ecosystem, observation of biomarkers and environmental parameters. Sclerochemistry is in its infancy and cannot be reliably used to provide insights into the pollution history recorded in shells. Alteration processes and mineral crystallization on the inner shell surface are presented here as a perspective tool for environmental studies.     

Spatiotemporal variation of macroinvertebrates in relation to canopy cover and other environmental factors in Eriora River, Niger Delta, Nigeria

Canopy cover is well known to influence the distribution of macroinvertebrates in temperate streams. Very little is known about how this factor influences stream communities in Afrotropical streams. The effects and possible interactions of environmental factors and canopy cover on macroinvertebrate community structure (abundance, richness, and diversity) were examined in four stations in Eriora River, southern Nigeria bimonthly from May to November 2010. The river supported diverse macroinvertebrates in which the upstream sampling stations with dense canopy cover were dominated by Decapoda, Ephemeroptera, Odonata, Gastropoda, Trichoptera, and Coleoptera while Diptera and Coleoptera were the benthic organisms found predominant at downstream stations with less canopy cover. Some caddisfly species such as Agapetus agilis, Trichosetodes species and the stonefly Neoperla species were present upstream and were found to be potential bioindicators for a clean ecosystem. The blood worm Chironomus species and Tabanus sp. were abundant at the downstream of the river and are considered potential bioindicators for an organically degrading ecosystem. Some environmental factors varied temporally with significantly higher macroinvertebrate abundance and richness in May. We found out that canopy cover and environmental factors affected macroinvertebrates abundance, diversity, and richness and that the individual taxon had varying responses to these factors. These results help identify the mechanisms underlying the effects of canopy cover and other environmental factors on Afrotropical stream invertebrate communities.     

Forecasting Peak Daily Ozone Levels: Part 2—A Regression with Time Series Errors Model Having a Principal Component Trigger to Forecast 1999 and 2002 Ozone Levels

Abstract

A modified time series approach, a Box-Jenkins regression with time series errors (RTSE) model plus a principal component (PC) trigger, has been developed to forecast peak daily 1-hr ozone (O₃) in real time at the University of Wisconsin-Milwaukee North (UWM-N) during 1999 and 2002. The PC trigger acts as a predictor variable in the RTSE model. It tries to answer the question: will the next day be a possible high O₃ day? To answer this question, three PC trigger rules were developed: (1) Hi-Low Checklist, (2) Discriminant Function Approach I, and (3) Discriminant Function Approach II. Also, a pure RTSE model without including the PC trigger and a persistence approach were tested for comparison. The RTSE model with DFA I successfully forecast the only two 1-hr federal exceedances (124 ppb), one in 1999 and one in 2002. In terms of the O₃ 100-ppb exceedances, 60–80% of the incorrect forecasts occurred with incorrect PC decisions. A few others may have been caused by unexpected O_3- weather relations. When the three approaches used UWM-N data to forecast a 100-ppb exceedance somewhere in the Milwaukee, WI, metropolitan area, their performance was dramatically improved: the false alarm rate was reduced from 0.89 to 0.44, and the probability of detection was increased from 0.71 to 0.88.     

Immobilization of mercury by pyrite (FeS2)

Elemental mercury (Hg⁰) is a metal with a number of atypical properties, which has resulted in its use in myriad anthropogenic processes. However, these same properties have also led to severe local subsurface contamination at many places where it has been used. As such, we studied the influence of various parameters on Hg(II) sorption onto pyrite (pH, time, Hg(II) concentration), a potential subsurface reactive barrier. Batch sorption studies revealed that total Hg(II) removal increases with both pH and time. X-ray absorption spectroscopy analysis showed that a transformation in the coordination environment at low pH occurred during aging over 2 weeks, to form an ordered monolayer of monodentate Hg-Cl complexes on pyrite. In column studies packed with pure quartz sand, the transport of Hg(II) was significantly retarded by the presence of a thin pyrite-sand reactive barrier, although dissolved oxygen inhibited Hg(II) sorption onto pyrite in the column.     

Sub-cooled and flashing liquid jets and droplet dispersion I. Overview and model implementation/validation

Many accidents involve two-phase releases of hazardous chemicals into the atmosphere. This paper describes the results of a third phase of a Joint Industry Project (JIP) on liquid jets and two-phase droplet dispersion. The aim of the project is to increase the understanding of the behaviour of sub-cooled non-flashing and superheated flashing liquid jets, and to improve the prediction of initial droplet size, droplet dispersion and rainout.Phase III of the JIP first included scaled experiments for materials with a range of volatilities (water, cyclohexane, butane, propane and gasoline). These experiments were carried out by Cardiff University including measurements of flow rate and initial droplet size across the full relevant range of superheats. See the companion paper II for further details of these experiments and the derivation of new refined correlations for droplet size distribution and Sauter Mean Diameter. Furthermore large-scale butane experiments were carried out by INERIS (France) to ensure that for more realistic scenarios the derived droplet size correlations are accurate.Model validation and model improvements were carried out by DNV Software, including validation of release rate and initial droplet size against the above scaled and large-scale experiments. New correlations for droplet size distribution and Sauter Mean Diameter (SMD) were implemented into the Phast discharge model. These were compared against a range of other droplet size and rainout correlations published in the literature, in conjunction with validation against an extensive set of experiments. It was shown that the new droplet size correlation agrees better against experimental data than the existing Phast correlation. To further improve the rainout prediction, the Phast dispersion model (UDM) was also extended to allow simultaneous modelling of a range of droplet sizes and distributed rainout (rather than rainout at one point).