17 resultados para risk assessments

em CentAUR: Central Archive University of Reading - UK


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A wide variety of exposure models are currently employed for health risk assessments. Individual models have been developed to meet the chemical exposure assessment needs of Government, industry and academia. These existing exposure models can be broadly categorised according to the following types of exposure source: environmental, dietary, consumer product, occupational, and aggregate and cumulative. Aggregate exposure models consider multiple exposure pathways, while cumulative models consider multiple chemicals. In this paper each of these basic types of exposure model are briefly described, along with any inherent strengths or weaknesses, with the UK as a case study. Examples are given of specific exposure models that are currently used, or that have the potential for future use, and key differences in modelling approaches adopted are discussed. The use of exposure models is currently fragmentary in nature. Specific organisations with exposure assessment responsibilities tend to use a limited range of models. The modelling techniques adopted in current exposure models have evolved along distinct lines for the various types of source. In fact different organisations may be using different models for very similar exposure assessment situations. This lack of consistency between exposure modelling practices can make understanding the exposure assessment process more complex, can lead to inconsistency between organisations in how critical modelling issues are addressed (e.g. variability and uncertainty), and has the potential to communicate mixed messages to the general public. Further work should be conducted to integrate the various approaches and models, where possible and regulatory remits allow, to get a coherent and consistent exposure modelling process. We recommend the development of an overall framework for exposure and risk assessment with common approaches and methodology, a screening tool for exposure assessment, collection of better input data, probabilistic modelling, validation of model input and output and a closer working relationship between scientists and policy makers and staff from different Government departments. A much increased effort is required is required in the UK to address these issues. The result will be a more robust, transparent, valid and more comparable exposure and risk assessment process. (C) 2006 Elsevier Ltd. All rights reserved.

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This report provides case studies of Early Warning Systems (EWSs) and risk assessments encompassing three main hazard types: drought; flood and cyclone. The case studies are taken from ten countries across three continents (focusing on Africa, South Asia and the Caribbean). The case studies have been developed to assist the UK Department for International Development (DFID) to prioritise areas for Early Warning System (EWS) related research under their ‘Science for Humanitarian Emergencies and Resilience’ (SHEAR) programme. The aim of these case studies is to ensure that DFID SHEAR research is informed by the views of Non-Governmental Organisations (NGOs) and communities engaged with Early Warning Systems and risk assessments (including community-based Early Warning Systems). The case studies highlight a number of challenges facing Early Warning Systems (EWSs). These challenges relate to financing; integration; responsibilities; community interpretation; politics; dissemination; accuracy; capacity and focus. The case studies summarise a number of priority areas for EWS related research: • Priority 1: Contextualising and localising early warning information • Priority 2: Climate proofing current EWSs • Priority 3: How best to sustain effective EWSs between hazard events? • Priority 4: Optimising the dissemination of risk and warning information • Priority 5: Governance and financing of EWSs • Priority 6: How to support EWSs under challenging circumstances • Priority 7: Improving EWSs through monitoring and evaluating the impact and effectiveness of those systems

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Systematic review (SR) is a rigorous, protocol-driven approach designed to minimise error and bias when summarising the body of research evidence relevant to a specific scientific question. Taking as a comparator the use of SR in synthesising research in healthcare, we argue that SR methods could also pave the way for a “step change” in the transparency, objectivity and communication of chemical risk assessments (CRA) in Europe and elsewhere. We suggest that current controversies around the safety of certain chemicals are partly due to limitations in current CRA procedures which have contributed to ambiguity about the health risks posed by these substances. We present an overview of how SR methods can be applied to the assessment of risks from chemicals, and indicate how challenges in adapting SR methods from healthcare research to the CRA context might be overcome. Regarding the latter, we report the outcomes from a workshop exploring how to increase uptake of SR methods, attended by experts representing a wide range of fields related to chemical toxicology, risk analysis and SR. Priorities which were identified include: the conduct of CRA-focused prototype SRs; the development of a recognised standard of reporting and conduct for SRs in toxicology and CRA; and establishing a network to facilitate research, communication and training in SR methods. We see this paper as a milestone in the creation of a research climate that fosters communication between experts in CRA and SR and facilitates wider uptake of SR methods into CRA.

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Ecological risk assessments must increasingly consider the effects of chemical mixtures on the environment as anthropogenic pollution continues to grow in complexity. Yet testing every possible mixture combination is impractical and unfeasible; thus, there is an urgent need for models that can accurately predict mixture toxicity from single-compound data. Currently, two models are frequently used to predict mixture toxicity from single-compound data: Concentration addition and independent action (IA). The accuracy of the predictions generated by these models is currently debated and needs to be resolved before their use in risk assessments can be fully justified. The present study addresses this issue by determining whether the IA model adequately described the toxicity of binary mixtures of five pesticides and other environmental contaminants (cadmium, chlorpyrifos, diuron, nickel, and prochloraz) each with dissimilar modes of action on the reproduction of the nematode Caenorhabditis elegans. In three out of 10 cases, the IA model failed to describe mixture toxicity adequately with significant or antagonism being observed. In a further three cases, there was an indication of synergy, antagonism, and effect-level-dependent deviations, respectively, but these were not statistically significant. The extent of the significant deviations that were found varied, but all were such that the predicted percentage effect seen on reproductive output would have been wrong by 18 to 35% (i.e., the effect concentration expected to cause a 50% effect led to an 85% effect). The presence of such a high number and variety of deviations has important implications for the use of existing mixture toxicity models for risk assessments, especially where all or part of the deviation is synergistic.

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The time at which the signal of climate change emerges from the noise of natural climate variability (Time of Emergence, ToE) is a key variable for climate predictions and risk assessments. Here we present a methodology for estimating ToE for individual climate models, and use it to make maps of ToE for surface air temperature (SAT) based on the CMIP3 global climate models. Consistent with previous studies we show that the median ToE occurs several decades sooner in low latitudes, particularly in boreal summer, than in mid-latitudes. We also show that the median ToE in the Arctic occurs sooner in boreal winter than in boreal summer. A key new aspect of our study is that we quantify the uncertainty in ToE that arises not only from inter-model differences in the magnitude of the climate change signal, but also from large differences in the simulation of natural climate variability. The uncertainty in ToE is at least 30 years in the regions examined, and as much as 60 years in some regions. Alternative emissions scenarios lead to changes in both the median ToE (by a decade or more) and its uncertainty. The SRES B1 scenario is associated with a very large uncertainty in ToE in some regions. Our findings have important implications for climate modelling and climate policy which we discuss.

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Currently, there are limited published data for the population dynamics of antimicrobial-resistant commensal bacteria. This study was designed to evaluate both the proportions of the Escherichia coli populations that are resistant to ampicillin at the level of the individual chicken on commercial broiler farms and the feasibility of obtaining repeated measures of fecal E. coli concentrations. Short-term temporal variation in the concentration of fecal E. coli was investigated, and a preliminary assessment was made of potential factors involved in the shedding of high numbers of ampicillin-resistant E. coli by growing birds in the absence of the use of antimicrobial drugs. Multilevel linear regression modeling revealed that the largest component of random variation in log-transformed fecal E. coli concentrations was seen between sampling occasions for individual birds. The incorporation of fixed effects into the model demonstrated that the older, heavier birds in the study were significantly more likely (P = 0.0003) to shed higher numbers of ampicillin-resistant E. coli. This association between increasing weight and high shedding was not seen for the total fecal E. coli population (P = 0.71). This implies that, in the absence of the administration of antimicrobial drugs, the proportion of fecal E. coli that was resistant to ampicillin increased as the birds grew. This study has shown that it is possible to collect quantitative microbiological data on broiler farms and that such data could make valuable contributions to risk assessments concerning the transfer of resistant bacteria between animal and human populations.

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European climate exhibits variability on a wide range of timescales. Understanding the nature and drivers of this variability is an essential step in developing robust climate predictions and risk assessments. The Atlantic Ocean has been suggested as an important driver of variability in European climate on decadal timescales1, but the importance of this influence in recent decades has been unclear, partly because of difficulties in separating the influence of the Atlantic Ocean from other contributions, for example, from the tropical Pacific Ocean and the stratosphere. Here we analyse four data sets derived from observations to show that, during the 1990s, there was a substantial shift in European climate towards a pattern characterized by anomalously wet summers in northern Europe, and hot, dry, summers in southern Europe, with related shifts in spring and autumn. These changes in climate coincided with a substantial warming of the North Atlantic Ocean, towards a state last seen in the 1950s. The patterns of European climate change in the 1990s are consistent with earlier changes attributed to the influence of the North Atlantic Ocean, and provide compelling evidence that the Atlantic Ocean was the key driver. Our results suggest that the recent pattern of anomalies in European climate will persist as long as the North Atlantic Ocean remains anomalously warm.

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Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants that frequently accumulate in soils. There is therefore a requirement to determine their levels in contaminated environments for the purposes of determining impacts on human health. PAHs are a suite of individual chemicals, and there is an ongoing debate as to the most appropriate method for assessing the risk to humans from them. Two methods predominate: the surrogate marker approach and the toxic equivalency factor. The former assumes that all chemicals in a mixture have an equivalent toxicity. The toxic equivalency approach estimates the potency of individual chemicals relative to the usually most toxic Benzo(a)pyrene. The surrogate marker approach is believed to overestimate risk and the toxic equivalency factor to underestimate risk. When analysing the risks from soils, the surrogate marker approach is preferred due to its simplicity, but there are concerns because of the potential diversity of the PAH profile across the range of impacted soils. Using two independent data sets containing soils from 274 sites across a diverse range of locations, statistical analysis was undertaken to determine the differences in the composition of carcinogenic PAH between site locations, for example, rural versus industrial. Following principal components analysis, distinct population differences were not seen between site locations in spite of large differences in the total PAH burden between individual sites. Using all data, highly significant correlations were seen between BaP and other carcinogenic PAH with the majority of r2 values > 0.8. Correlations with the European Food Standards Agency (EFSA) summed groups, that is, EFSA2, EFSA4 and EFSA8 had even higher correlations (r2 > 0.95). We therefore conclude that BaP is a suitable surrogate marker to represent mixtures of PAH in soil during risk assessments.

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Bioaccessibility tests can be used to improve contaminated land risk assessments. For organic pollutants a ‘sink’ is required within these tests to better mimic their desorption under the physiological conditions prevailing in the intestinal tract, where a steep diffusion gradient for the removal of organic pollutants from the soil matrix would exist. This is currently ignored in most PBET systems. By combining the CEPBET bioaccessibility test with an infinite sink, the removal of PAH from spiked solutions was monitored. Less than 10% of spiked PAH remained in the stomach media after 1 h, 10% by 4 h in the small intestine compartment and c.15% after 16 h in the colon. The addition of the infinite sink increased bioaccessibility estimates for field soils by a factor of 1.2–2.8, confirming its importance for robust PBET tests. TOC or BC were not the only factors controlling desorption of the PAH from the soils.

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1. Pollinating insects provide crucial and economically important ecosystem services to crops and wild plants, but pollinators, particularly bees, are globally declining as a result of various driving factors, including the prevalent use of pesticides for crop protection. Sublethal pesticide exposure negatively impacts numerous pollinator lifehistory traits, but its influence on reproductive success remains largely unknown. Such information is pivotal, however, to our understanding of the long-term effects on population dynamics. 2 We investigated the influence of field-realistic trace residues of the routinely used neonicotinoid insecticides thiamethoxam and clothianidin in nectar substitutes on the entire life-time fitness performance of the red mason bee Osmia bicornis. 3 We show that chronic, dietary neonicotinoid exposure has severe detrimental effects on solitary bee reproductive output. Neonicotinoids did not affect adult bee mortality; however, monitoring of fully controlled experimental populations revealed that sublethal exposure resulted in almost 50% reduced total offspring production and a significantly male-biased offspring sex ratio. 4 Our data add to the accumulating evidence indicating that sublethal neonicotinoid effects on non-Apis pollinators are expressed most strongly in a rather complex, fitness-related context. Consequently, to fully mitigate long-term impacts on pollinator population dynamics, present pesticide risk assessments need to be expanded to include whole life-cycle fitness estimates, as demonstrated in the present study using O. bicornis as a model.

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Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

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The use of potent anticogulant rodenticide ‘resistance-breakers’ is avoided due to their higher toxicity and potential to be more hazardous in the environment [6]. However, in areas where practitioners seek to control resistant rodent infestations, their use may pose less of a risk than applications of ineffective baits. Compounds to which rodents are resistant to, do not provide effective control and create a long-term source of AR in the environment. The higher quantities of anticoagulant rodenticide used show that using ineffective compounds may extend both the period and severity of exposure to non-target animals to anticoagulant rodenticides. Conversely the effective use of resistance-breakers to control anticoagulant rodenticide-resistant rat populations results in lower environmental exposure of anticoagulant rodenticides for non-targets. Of course, the relative toxicity of the different anticoagulant rodenticides will also play an important part in overall risk assessments. However, this can be outweighed by the relative exposure to different anticoagulant rodenticides in such situations.

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A range of wastes representative of materials currently applied, or with future potential to be applied, to agricultural land in the UK as fertilisers and soil improvers or used as animal bedding in livestock production, were investigated. In addition to full physico-chemical characterization, the materials were analysed for a suite of priority organic contaminants. In general, contaminants were present at relatively low concentrations. For example, polychlorinated dibenzo-p-dioxins/dibenzofurans and polychlorinated biphenyls in biosolids and compost-like-outputs (CLOs) were, in most cases, between 5-50 times lower than proposed and implemented European limit values for biosolids or composts applied to agricultural land. However, the technical basis for these limits may need to be re-evaluated. Polybrominated, and mixed halogenated, dibenzo-p-dioxins/dibenzofurans are not currently considered in risk assessments of dioxins and dioxin-like chemicals, but were detected in the biosolids and compost-like-outputs and their potential contribution to the overall toxic equivalency will be assessed. Other, ‘emerging’ contaminants such as perfluoralkyl compounds (PFCs) and organophosphate flame retardants were detected in several of the waste materials, and their potential significance is discussed. The study is part of a wider research programme that will provide evidence to improve confidence in the use of waste-derived materials in agriculture and establish guidelines to protect the food chain where necessary.

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Although the use of climate scenarios for impact assessment has grown steadily since the 1990s, uptake of such information for adaptation is lagging by nearly a decade in terms of scientific output. Nonetheless, integration of climate risk information in development planning is now a priority for donor agencies because of the need to prepare for climate change impacts across different sectors and countries. This urgency stems from concerns that progress made against Millennium Development Goals (MDGs) could be threatened by anthropogenic climate change beyond 2015. Up to this time the human signal, though detectable and growing, will be a relatively small component of climate variability and change. This implies the need for a twin-track approach: on the one hand, vulnerability assessments of social and economic strategies for coping with present climate extremes and variability, and, on the other hand, development of climate forecast tools and scenarios to evaluate sector-specific, incremental changes in risk over the next few decades. This review starts by describing the climate outlook for the next couple of decades and the implications for adaptation assessments. We then review ways in which climate risk information is already being used in adaptation assessments and evaluate the strengths and weaknesses of three groups of techniques. Next we identify knowledge gaps and opportunities for improving the production and uptake of climate risk information for the 2020s. We assert that climate change scenarios can meet some, but not all, of the needs of adaptation planning. Even then, the choice of scenario technique must be matched to the intended application, taking into account local constraints of time, resources, human capacity and supporting infrastructure. We also show that much greater attention should be given to improving and critiquing models used for climate impact assessment, as standard practice. Finally, we highlight the over-arching need for the scientific community to provide more information and guidance on adapting to the risks of climate variability and change over nearer time horizons (i.e. the 2020s). Although the focus of the review is on information provision and uptake in developing regions, it is clear that many developed countries are facing the same challenges. Copyright © 2009 Royal Meteorological Society

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The development of emotional regulation capacities in children at high versus low risk for externalizing disorder was examined in a longitudinal study investigating: a) whether disturbances in emotion regulation precede and predict the emergence of externalizing symptoms; and b) whether sensitive maternal behavior is a significant influence on the development of child emotion regulation. Families experiencing high (n=58) and low (n=63) levels of psychosocial adversity were recruited to the study during pregnancy. Direct observational assessments of child emotion regulation capacities and maternal sensitivity were completed in early infancy, at 12 and 18-months, and at 5-years. Key findings were as follows. First, high risk children showed poorer emotion regulation capacities than their low risk counterparts at every stage of assessment. Second, from 12-months onwards, emotion regulation capacities showed a degree of stability, and were associated with behavioral problems, both concurrently and prospectively. Third, maternal sensitivity was related to child emotion regulation capacities throughout development, with poorer emotion regulation in the high risk group being associated with lower maternal sensitivity. The results are consistent with a causal role for problems in the regulation of negative emotions in the etiology of externalizing psychopathology, and highlight insensitive parenting as a potentially key developmental influence.