989 resultados para Environmental Pollutants


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The increasing incidence of children identified and diagnosed with Autism Spectrum Disorders (ASD) and other developmental disabilities (DD) poses a major challenge to Title V and other programs as they try to meet the diverse and sometimes complex needs of these children. However, those state that have initiated coordinated efforts to meet the needs of these children cross systems have had the opportunity to form and/or strengthen relationships with new partners. In addition, these coordinated efforts will allow states to develop new policies, programs and financing mechanisms addressing the health of children with ASD, which may also strengthen the system of care for all Children and Youth with Special Health Care Needs.

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This brochure contains information on the environmental information available at the Macbride Nature Recreation Area including programs on cycles and inter-relationships in nature, wildlife adaptations and survival, life in the forest community, patterns and changes in autumn, flowers insects and the renewal of spring, lives of birds and raptor information geared for elementary aged children.

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The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.

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[spa] En este artículo aplicamos un modelo input-output ampliado medioambientalmente para analizar un aspecto específico de la hipótesis de la curva de Kuznets ambiental. El propósito del estudio es analizar si las estructuras de consumo de los hogares con una mejor ‘posición económica’ pueden tener un efecto positivo para reducir las presiones medioambientales. Para ello combinamos información de diferentes bases de datos para analizar el impacto de la contaminación atmosférica del consumo de diferentes hogares españoles en el año 2000. Consideramos nueve gases, i.e. los seis gases de efecto invernadero (CO2, CH4, N2O, SF6, HFCs, y PFCs) y otros tres gases (SO2, NOx, y NH3). Clasificamos los hogares en quintiles de gasto per capita y quintiles de gasto equivalente. Los resultados obtenidos muestran que hay una relación positiva y elevada entre el nivel de gasto y las emisiones directas e indirectas generadas por el consumo de los hogares; sin embargo, las intensidades de emisión tienden a disminuir con el nivel de gasto para los diferentes gases, con la excepción de SF6, HFCs, y PFCs.

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Genetically constructed microbial biosensors for measuring organic pollutants are mostly applied in aqueous samples. Unfortunately, the detection limit of most biosensors is insufficient to detect pollutants at low but environmentally relevant concentrations. However, organic pollutants with low levels of water solubility often have significant gas-water partitioning coefficients, which in principle makes it possible to measure such compounds in the gas rather than the aqueous phase. Here we describe the first use of a microbial biosensor for measuring organic pollutants directly in the gas phase. For this purpose, we reconstructed a bioluminescent Pseudomonas putida naphthalene biosensor strain to carry the NAH7 plasmid and a chromosomally inserted gene fusion between the sal promoter and the luxAB genes. Specific calibration studies were performed with suspended and filter-immobilized biosensor cells, in aqueous solution and in the gas phase. Gas phase measurements with filter-immobilized biosensor cells in closed flasks, with a naphthalene-contaminated aqueous phase, showed that the biosensor cells can measure naphthalene effectively. The biosensor cells on the filter responded with increasing light output proportional to the naphthalene concentration added to the water phase, even though only a small proportion of the naphthalene was present in the gas phase. In fact, the biosensor cells could concentrate a larger proportion of naphthalene through the gas phase than in the aqueous suspension, probably due to faster transport of naphthalene to the cells in the gas phase. This led to a 10-fold lower detectable aqueous naphthalene concentration (50 nM instead of 0.5 micro M). Thus, the use of bacterial biosensors for measuring organic pollutants in the gas phase is a valid method for increasing the sensitivity of these valuable biological devices.

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Les deux premières parties de cet article parues précédemment ont présenté la méthodologie ainsi que les premiers éléments du bilan réalisé sur la période allant de 2009 à 2012 de la veille bibliographique sur la surveillance biologique de l'exposition aux produits chimiques en milieu de travail (SBEPC MT) mise en place par un réseau francophone multidisciplinaire.

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Objective Exposure to bioaerosols in the occupational environment of sawmills could be associated with a wide range of health effects, in particular respiratory impairment, allergy and organic dust toxic syndrome. The objective of the study was to assess the frequency of medical respiratory and general symptoms and their relation to bioaerosol exposure. Method Twelve sawmills in the French part of Switzerland were investigated and the relationship between levels of bioaerosols (wood dust, airborne bacteria, airborne fungi and endotoxins), medical symptoms and impaired lung function was explored. A health questionnaire was distributed to 111 sawmill workers. Results The concentration of airborne fungi exceeded the limit recommended by the Swiss National Insurance (SUVA) in the twelve sawmills. This elevated fungi level significantly influenced the occurrence of bronchial syndrome (defined by cough and expectorations). No other health effects (irritations or respiratory effects) could be associated to the measured exposures. We observed that junior workers showed significantly more irritation syndrome (defined by itching/running nose, snoring and itching/red eyes) than senior workers. Lung function tests were not influenced by bioaerosol levels nor dust exposure levels. Conclusion Results suggest that occupational exposure to wood dust in a Swiss sawmill does not promote a clinically relevant decline in lung function. However, the occurrence of bronchial syndrome is strongly influenced by airborne fungi levels. [Authors]

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This Environmental Assessment documents the National Environmental Policy Act (NEPA) process for developing a Comprehensive Conservation Plan (CCP) for the Iowa Wetland Management District (WMD, district). In general, scoping reveals issues that drive alternative ways of managing the district. Implementation of each of those alternative management styles (including the No Action Alternative) may have different effects on the physical, biological, and socio-economic environment. Analysis of these effects reveals the “preferred” alternative, which constitutes the CCP. The CCP includes goals, objectives, and strategies for the district to guide overall management for the next 15 years. The Iowa WMD consists of scattered tracts of habitat (both wetland and upland grassland) known as Waterfowl Production Areas (WPAs). As of 2011, there are 75 WPAs in 18 counties in north-central Iowa totaling 24,712 acres in fee title primarily managed by the Iowa Department of Natural Resources (DNR). Even though district acquisition has only occurred in 18 counties to date, a larger 35-county boundary is approved. This boundary follows the historic range of the poorly drained Prairie Pothole Region (PPR) in Iowa, an area known for its waterfowl production. The district also includes 575 WPA acres and approximately 434 Farm Service Agency acres in conservation easements on private land. This plan was prepared with the intent that the strong partnership with the Iowa DNR will continue over the next 15 years.

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DESCRIPTION OF PROPOSED ACTION This Environmental Assessment (EA) has been prepared in compliance with the requirements of the National Environmental Policy Act of 1969 (NEPA). This EA informs the public and interested agencies of the proposed action and alternatives to the proposed action in order to gather feedback on the improvements under consideration. Proposed Action The Iowa Department of Transportation (Iowa DOT) and the Federal Highway Administration (FHWA) are evaluating potential alternatives to improve IA 122 in the City of Mason City. IA 122/Business US 18 is a primary east-west travel route through the City that transitions from a 4- lane undivided roadway, to 2-lane one-way pairs, then back to a 4-lane undivided roadway (Figure 1-1). The Iowa DOT proposes to flatten the tight reverse curves on the east end of the project. The one-way pairs will be narrowed by eliminating on-street parking along the corridor to more clearly define travel lanes. This will serve to calm traffic flows and reduce crashes along the highway. Additionally, improvements to intersections as well as consolidating or removing access points to improve traffic operations are proposed within the project corridor. A new access road for the Mason City Fire Department on the west end of the project will allow emergency trucks better access to travel south and east. Study Area The primary area of investigation for the Project is generally bounded by IA 122 through Mason City, known locally as 5th and 6th Street Southwest from South Monroe Avenue to South Carolina Avenue. US 65, known locally as Federal Avenue, bisects the study area. At this intersection of US 65 and Iowa 122, the 5th and 6th Street SW changes to 5th and 6th St SE. For the purposes of this discussion, this area will be referred to collectively as the IA 122 corridor. The Study Area boundaries were established to allow the development of a wide range of alternatives that could address the purpose and need for the project. The Study Area is larger than the area proposed for construction activities for the Project. However, some impacts may extend beyond the Study Area; where this occurs, it will be noted and addressed in the Environmental Analysis Section (Section 5). Figure 1-1 outlines the Study Area of the proposed action.

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Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.

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This guide provides a variety of tools that can help an educator, building staff or school district decide how to include environmental education in their curriculum.

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Les élevages d'animaux de rente hébergent de plus en plus de bêtes. Cette situation génère une accumulation de poussière organique, constituée de particules inertes et de microorganismes, issus de la nourriture, de la litière, des matières fécales, des pellicules de la peau, des poils, etc. L'activité des animaux et l'activité professionnelle favorisent une remise en suspension de cette poussière, qui peut se propager à l'extérieur. Ces émissions de particules organiques dans l'environnement soulèvent des inquiétudes pour la santé des riverains. Ces craintes sont légitimes, puisque les problèmes respiratoires, allergiques ou toxiques sont bien connus chez les travailleurs agricoles exposés à de fortes doses de poussières organiques. Un autre risque sanitaire lié aux élevages intensifs d'animaux est la dissémination de bactéries résistantes aux antibiotiques dans l'environnement avec, pour éventuelle conséquence, une transmission de ces souches aux personnes résidant à proximité. Cette problématique est bien connue dans les élevages de porcs fréquemment colonisés par des SARM (Staphylococcus aureus résistant à la méticilline), qui sont transmis aux éleveurs. Les deux études analysées ci-dessous ont investigué cette problématique de dissémination des particules organiques dans l'environnement et les conséquences sur la santé des riverains. La première a étudié le lien entre le fait de résider à proximité de fermes d'élevage d'animaux et la prévalence de maladies respiratoires. La deuxième a étudié le risque de colonisation nasale par des SARM dans une population de vétérans vivant à proximité d'élevages intensifs de porcs.

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The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.