Suchergebnisse

This article explores the use of an approach for setting default values for the noncancer toxicity, developed as part of the Threshold of Toxicological Concern (TTC), for the evaluation of the chronic noncarcinogenic effects of certain chemical mixtures. Individuals are exposed to many mixtures where there are little or no toxicological data on some or all of the mixture components. The approach developed in the TTC can provide a basis for conservative estimates of the toxicity of the mixture components when compound‐specific data are not available. The application of this approach to multiple chemicals in a mixture, however, has implications for the statistical assumptions made in developing component‐based estimates of mixtures. Specifically, conservative assumptions that are appropriate for one compound may become overly conservative when applied to all components of a mixture. This overestimation can be investigated by modeling the uncertainty in toxicity standards. In this article the approach is applied to both hypothetical and actual examples of chemical mixtures and the potential for overestimation is investigated. The results indicate that the use of the approach leads to conservative estimates of mixture toxicity and therefore its use is most appropriate for screening assessments of mixtures.

Health risk assessments have become so widely accepted in the United States that their conclusions are a major factor in many environmental decisions. Although the risk assessment paradigm is 10 years old, the basic risk assessment process has been used by certain regulatory agencies for nearly 40 years. Each of the four components of the paradigm has undergone significant refinements, particularly during the last 5 years. A recent step in the development of the exposure assessment component can be found in the 1992 EPA Guidelines for Exposure Assessment. Rather than assuming worst‐case or hypothetical maximum exposures, these guidelines are designed to lead to an accurate characterization, making use of a number of scientific advances. Many exposure parameters have become better defined, and more sensitive techniques now exist for measuring concentrations of contaminants in the environnment. Statistical procedures for characterizing variability, using Monte Carlo or similar approaches, eliminate the need to select point estimates for all individual exposure parameters. These probabilistic models can more accurately characterize the full range of exposures that may potentially be encountered by a given population at a particular site, reducing the need to select highly conservative values to account for this form of uncertainty in the exposure estimate. Lastly, our awareness of the uncertainties in the exposure assessment as well as our knowledge as to how best to characterize them will almost certainly provide evaluations that will be more credible and, therein, more useful to risk managers. If these refinements are incorporated into future exposure assessments, it is likely that our resources will be devoted to problems that, when resolved, will yield the largest improvement in public health.

"Peatlands are wetlands whose soil comprises the undecomposed remains of plants that accumulate in such a way that both responds to, and controls, the flux and storage of surface water and groundwater within peatlands, and runoff to downstream ecosystems. Water tables are generally at or near the surface, at least for much of the year. As the largest global terrestrial store of carbon, peatlands strongly influence global climate. Depending on the setting, peatlands develop into distinct forms that peatland scientists generally categorize as bogs, fens and swamps with peat soils. Bogs have accumulated sufficient peat depth, mostly due to the abundance of Sphagnum mosses, that they become topographically isolated and receive water only via precipitation, thus shed surface water and groundwater. Bogs can have a typically sparse cover of stunted trees. Fens and peat swamps generally receive water and constituent dissolved ions from adjacent mineral terrains, although flow directions may reverse. As with bogs, the quantity and quality of water received controls their plant community function and structure and therefore their soil properties and ability to store and transmit groundwater. Fens generally have a steadier supply of water than swamps, and thus a more stable water table that favors sedges and brown mosses, and sometimes trees; swamps typically have a more episodic water exchange, thus variable water table, which is more favorable for woody vegetation. In peatlands, more recently formed thus less decomposed soils occur in the upper layers--these newer soils can have extremely high porosity (≤95%) and are typically more permeable (saturated hydraulic conductivity up to 10-1000 m/d), whereas soils deeper than 0.3-0.5 m generally have low hydraulic conductivity (≤0.5 m/d). Consequently, there is a transmissivity feedback that exacerbates surface- and groundwater flows when the water table is particularly high. Understanding their hydrology and water quality is key to effective land management where peatlands are common on the landscape."--

Purpose The purpose of this study was to 1) determine the demographic differences between adults who have accepted, or plan to accept, the COVID-19 vaccine and those who will not accept the COVID-19 vaccine and 2) describe the potential influencers in deciding to accept the COVID-19 vaccine among adults living in the United States who have accepted or plan to accept the vaccine. Design A cross-sectional design utilizing an online survey was deployed using social media and a crowdsourcing platform. Setting United States. Subjects One thousand three hundred ninety-five (1395) adults completed the survey. The majority were white, male, between the ages of 25 and 45, and with representation from 50 states and Puerto Rico. Measures A two-branched survey was used to assess demographic information, vaccination intention, and 19 potential influencers of COVID-19 vaccine acceptance. Analysis Analysis included descriptive statistics and Chi-square tests to determine differences between groups. Results A higher proportion of male ( P < .001), married ( P < .001), and college-educated ( P < .001) participants reported acceptance of the vaccine. The factors with the highest mean score of reported level of influence were duty to protect the vulnerable and contribution to move society back to a sense of normalcy. Conclusion Understanding the potential influencers of vaccine acceptance may provide insight into strategies that could increase vaccination uptake.

Abstract. The destructive nature of the  ∼  590 000 ha Horse river wildfire in the Western Boreal Plain (WBP), northern Alberta, in May of 2016 motivated the investigation of the hydrometeorological conditions that preceded the fire. Historical climate and field hydrometeorological data from a moderate-rich fen watershed were used to (a) identify whether the spring 2016 conditions were outside the range of natural variability for WBP climate cycles, (b) explain the observed patterns in burn severity across the watershed, and (c) identify whether fall and winter moisture signals observed in peatlands and lowland forests in the region are indicative of wildfire. Field hydrometeorological data from the fen watershed confirmed the presence of cumulative moisture deficits prior to the fire. Hydrogeological investigations highlighted the susceptibility of fen and upland areas to water table and soil moisture decline over rain-free periods (including winter), due to the watershed's reliance on supply from localized flow systems originating in topographic highs. Subtle changes in topographic position led to large changes in groundwater connectivity, leading to greater organic soil consumption by fire in wetland margins and at high elevations. The 2016 spring moisture conditions measured prior to the ignition of the fen watershed were not illustrated well by the Drought Code (DC) when standard overwintering procedures were applied. However, close agreement was found when default assumptions were replaced with measured duff soil moisture recharge and incorporated into the overwintering DC procedure. We conclude that accumulated moisture deficits dating back to the summer of 2015 led to the dry conditions that preceded the fire. The infrequent coinciding of several hydrometeorological conditions, including low autumn soil moisture, a modest snowpack, lack of spring precipitation, and high spring air temperatures and winds, ultimately led to the Horse river wildfire spreading widely and causing the observed burn patterns. Monitoring soil moisture at different land classes and watersheds would aid management strategies in the production of more accurate overwintered DC calculations, providing fire management agencies early warning signals ahead of severe spring wildfire seasons.

Exposure duration is an important component in determining long‐term dose rates associated with exposure to environmental contaminants. Surveys of exposed populations collect information on individuals' past behaviors, including the durations of a behavior up to the time of the survey. This paper presents an empirical approach for determining the distribution of total durations that is consistent with the distribution past durations obtained from surveys. This approach is appropriate where the rates of beginning and ending a behavior are relatively constant over time. The approach allows the incorporation of information on the distribution of age in a population into the determination of the distribution of durations. The paper also explores the impact of "longevity" bias on survey data. A case study of the application of this approach to two angler populations is also provided. The results of the case study have characteristics similar to the results reported by Israeli and Nelson (Risk Anal. 12, 65‐72 (1992)) from their analytical model of residential duration. Specifically, the average period of time for the total duration in the entire population is shorter than the average period of time reported for historical duration in the surveyed individuals.

Indirect exposures to 2,3,7,8‐tetrachlorodibenzo‐p‐dioxin (TCDD) and other toxic materials released in incinerator emissions have been identified as a significant concern for human health. As a result, regulatory agencies and researchers have developed specific approaches for evaluating exposures from indirect pathways. This paper presents a quantitative assessment of the effect of uncertainty and variation in exposure parameters on the resulting estimates of TCDD dose rates received by individuals indirectly exposed to incinerator emissions through the consumption of home‐grown beef. The assessment uses a nested Monte Carlo model that separately characterizes uncertainty and variation in dose rate estimates. Uncertainty resulting from limited data on the fate and transport of TCDD are evaluated, and variations in estimated dose rates in the exposed population that result from location‐specific parameters and individuals'behaviors are characterized. The analysis indicates that lifetime average daily dose rates for individuals living within 10 km of a hypothetical incinerator range over three orders of magnitude. In contrast, the uncertainty in the dose rate distribution appears to vary by less than one order of magnitude, based on the sources of uncertainty included in this analysis. Current guidance for predicting exposures from indirect exposure pathways was found to overestimate the intakes for typical and high‐end individuals.

AbstractA parental report questionnaire posted to a population sample of 18-month-old twins correctly assigned zygosity in 95%of cases when validated against zygosity determined by identity of polymorphic DNA markers. The questionnaire was as accurate when readministered at 3 years of age, with 96% of children being assigned the same zygosity on both occasions. The results validate the use of parental report questionnaire data to determine zygosity in infancy. Twin Research (2000) 3, 129–133.

ABSTRACTA recently introduced EC Directive requires that soils receiving sewage sludge should be sampled to a greater depth (250 mm) than previously.The Water Research Centre foresaw the difficulties that could arise for responsible Authorities if they were to cope with the extra workload and maintain the quality of sampling, and therefore it funded the development of an automatic sampler.This report traces the development of the sampler which was mounted on an all‐terrain vehicle, and illustrates its suitability for the task by reporting one year's operating experiences. Work rates have been up to eight times those with hand sampling.A production machine from the first batch is also described.

Determining the probabilistic limits for the uncertainty factors used in the derivation of the Reference Dose (RfD) is an important step toward the goal of characterizing the risk of noncarcinogenic effects from exposure to environmental pollutants. If uncertainty factors are seen, individually, as "upper bounds" on the dose‐scaling factor for sources of uncertainty, then determining comparable upper bounds for combinations of uncertainty factors can be accomplished by treating uncertainty factors as distributions, which can be combined by probabilistic techniques. This paper presents a conceptual approach to probabilistic uncertainty factors based on the definition and use of RfDs by the US. EPA. The approach does not attempt to distinguish one uncertainty factor from another based on empirical data or biological mechanisms but rather uses a simple displaced lognormal distribution as a generic representation of all uncertainty factors. Monte Carlo analyses show that the upper bounds for combinations of this distribution can vary by factors of two to four when compared to the fixed‐value uncertainty factor approach. The probabilistic approach is demonstrated in the comparison of Hazard Quotients based on RfDs with differing number of uncertainty factors.

This paper presents an approach for characterizing the probability of adverse effects occurring in a population exposed to dose rates in excess of the Reference Dose (RfD). The approach uses a linear threshold (hockey stick) model of response and is based on the current system of uncertainty factors used in setting RfDs. The approach requires generally available toxicological estimates such as No‐Observed‐Adverse‐Effect Levels (NOAELs) or Benchmark Doses and doses at which adverse effects are observed in 50% of the test animals (ED50s). In this approach, Monte Carlo analysis is used to characterize the uncertainty in the dose response slope based on the range and magnitude of the key sources of uncertainty in setting protective doses. The method does not require information on the shape of the dose response curve for specific chemicals, but is amenable to the inclusion of such data. The approach is applied to four compounds to produce estimates of response rates for dose rates greater than the RfD