981 resultados para Environmental accounting
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Peixoto de Azevedo is located in the north of State of Mato Grosso, where environmental alterations led to an outbreak of American cutaneous leishmaniasis in the 80s. The parasite from patients was characterized as Leishmania (V.) braziliensis. The aim of this study is to contribute to the sand fly ecology of Central-West Brazil. Captures were carried out monthly using CDC light traps. Twenty-six species of sand fly were characterized; among which Lutzomyia (Lutzomyia) spathotrichia, L. runoides and L. (Psychodopygus) llanosmartinsi were recorded in the State of Mato Grosso for the first time. L. (Nyssomyia) whitmani, L. (N.) antunesi, L. (L.) spathotrichia, L. (P.) c. carrerai, L. (P.) complexa, L. (P.) lainsoni and L. (N.) umbratilis constituted 92.4% of the local fauna, among which L. (N.) whitmani and L. (N.) antunesi, accounting for about 53% of the fauna at the stations of capture. On the vertical distribution of sand flies on the Beira-Rio Farm, L. (N.) whitmani and L. (N.) antunesi prevailed at ground level and in the canopy, respectively, whereas on the BR-080, L. (P.) llanosmartinsi was prevalent on the ground and L. (P.) c. carrerai, in the canopy. It is suggested that L. (N.) umbratilis is the local vector.
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The immature stages of Ochlerotatus albifasciatus develop in temporary pools. The present study aims at evaluating the seasonal dynamics of the aquatic stages of this mosquito, also analyzing the relationship among their presence and breeding success to some relevant climatic and environmental variables in the ephemeral rain pools of an urban park. Nineteen cohorts of O. albifasciatus that developed synchronously after rain events were recorded in all seasons. The proportions of mosquito-positive pools were significantly higher during the fall-winter period than in the spring-summer months (p < 0.001). The presence of this mosquito species was positively related to the amount of rain (p < 0.001), whereas negatively correlated to air temperature (p < 0.05) within a 5.2 to 29.7ºC range. The distribution of the number of cohorts per pool throughout the year was grouped (variance/mean: 3.96), indicating that these habitats were not equally suitable as breeding sites. The immature stages of O. albifasciatus were detected in pools belonging to all of the categories of surface area, depth, duration, vegetation cover, and insolation. However, the proportion of pools where immature mosquitoes were detected was positively and significantly related to surface, depth, duration, and vegetation cover. On the other hand, the proportion of mosquito-positive pools was higher at an intermediate insolation degree. Our results suggest that although preimaginal stages were present in all seasons, high temperatures may be unfavorable to larval development, and substrate vegetation may regulate water temperature. The positive relationship between the proportion of mosquito-positive pools and pool size and duration might reflect a strategy of O. albifasciatus to accomplish immature development.
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The Urn Sohryngkew section of Meghalaya, NE India, located 800-1000 km from the Deccan volcanic province, is one of the most complete Cretaceous-Tertiary boundary (KTB) transitions worldwide with all defining and supporting criteria present: mass extinction of planktic foraminifera, first appearance of Danian species, delta(13)C shift, Ir anomaly (12 ppb) and KTB red layer. The geochemical signature of the KTB layer indicates not only an extraterrestrial signal (Ni and all Platinum Group Elements (PGEs)) of a second impact that postdates Chicxulub, but also a significant component resulting from condensed sedimentation (P), redox fluctuations (As, Co, Fe, Pb, Zn, and to a lesser extent Ni and Cu) and volcanism. From the late Maastrichtian C29r into the early Danian, a humid climate prevailed (kaolinite: 40-60%, detrital minerals: 50-80%). During the latest Maastrichtian, periodic acid rains (carbonate dissolution; CIA index: 70-80) associated with pulsed Deccan eruptions and strong continental weathering resulted in mesotrophic waters. The resulting super-stressed environmental conditions led to the demise of nearly all planktic foraminiferal species and blooms (>95%) of the disaster opportunist Guembelitria cretacea. These data reveal that detrimental marine conditions prevailed surrounding the Deccan volcanic province during the main phase of eruptions in C29r below the KTB. Ultimately these environmental conditions led to regionally early extinctions followed by global extinctions at the KTB. (C) 2011 Elsevier B.V. All rights reserved.
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Study of certain accounting issues related to the HSE (Considine Report) Click here to download PDF 759kb
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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.
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The incidence of neurodegenerative disease like Parkinson's disease and Alzheimer's disease (AD) increases dramatically with age; only a small percentage is directly related to familial forms. The etiology of the most abundant, sporadic forms is complex and multifactorial, involving both genetic and environmental factors. Several environmental pollutants have been associated with neurodegenerative disorders. The present article focuses on results obtained in experimental neurotoxicology studies that indicate a potential pathogenic role of lead and mercury in the development of neurodegenerative diseases. Both heavy metals have been shown to interfere with a multitude of intracellular targets, thereby contributing to several pathogenic processes typical of neurodegenerative disorders, including mitochondrial dysfunction, oxidative stress, deregulation of protein turnover, and brain inflammation. Exposure to heavy metals early in development can precondition the brain for developing a neurodegenerative disease later in life. Alternatively, heavy metals can exert their adverse effects through acute neurotoxicity or through slow accumulation during prolonged periods of life. The pro-oxidant effects of heavy metals can exacerbate the age-related increase in oxidative stress that is related to the decline of the antioxidant defense systems. Brain inflammatory reactions also generate oxidative stress. Chronic inflammation can contribute to the formation of the senile plaques that are typical for AD. In accord with this view, nonsteroidal anti-inflammatory drugs and antioxidants suppress early pathogenic processes leading to Alzheimer's disease, thus decreasing the risk of developing the disease. The effects of lead and mercury were also tested in aggregating brain-cell cultures of fetal rat telencephalon, a three-dimensional brain-cell culture system. The continuous application for 10 to 50 days of non-cytotoxic concentrations of heavy metals resulted in their accumulation in brain cells and the occurrence of delayed toxic effects. When applied at non-toxic concentrations, methylmercury, the most common environmental form of mercury, becomes neurotoxic under pro-oxidant conditions. Furthermore, lead and mercury induce glial cell reactivity, a hallmark of brain inflammation. Both mercury and lead increase the expression of the amyloid precursor protein; mercury also stimulates the formation of insoluble beta-amyloid, which plays a crucial role in the pathogenesis of AD and causes oxidative stress and neurotoxicity in vitro. Taken together, a considerable body of evidence suggests that the heavy metals lead and mercury contribute to the etiology of neurodegenerative diseases and emphasizes the importance of taking preventive measures in this regard.
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The variation of abundances of intermediate snail hosts of Fasciola hepatica in Cuba (Fossaria cubensis and Pseudosuccinea columella) was studied during one year under natural conditions at five sampling sites in San Juan y Martinez municipality, Pinar del Rio province, Cuba. The effect of some environmental variables on the lymnaeid abundances was also studied. A canonical correspondence analysis showed that both species do not generally occur together in the same habitat and that most factors affect them in an opposite fashion, although both of them correlate positively through time to the diversity of the habitats. F. cubensis prefers the sites that are in or closer to the city whereas P. columella is more abundant in rural sites. Lymnaeid abundances are mainly affected by nitrite and nitrate concentrations as well as by the abundance of the thiarid Tarebia granifera. F. cubensis is more abundant in polluted habitats with low densities (or absence) of T. granifera whereas P. columella prefers cleaner habitats and can coexist with the thiarid, even at its higher densities. The implications of divergent preferences of the two lymnaeids for the control of fasciolosis are discussed.
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This paper examines the distribution and infection of Biomphalaria glabrata with Schistosoma mansoni in all aquatic snail habitats in a rural area in the state of Minas Gerais, Brazil, in relation to physico/biotic and behavioral factors. Snail and environmental surveys were carried out semi-annually between July 2001 and November 2002 at 106 sites. Collected snails were examined in the laboratory for infection. B. glabrata densities were highest in overflow ponds, irrigation ponds, springs, canals and wells, and lowest in fishponds and water tanks. Snail densities were higher during the hot, rainy season except for streams and canals and were statistically associated with the presence of fish, pollution, and vegetation density. Tilapia fish and an unidentified Diptera larva were found to be predators of B. glabrata but ducks were not. Twenty-four of the 25 infected snails were collected in 2001(1.4% infection rate) and only one in 2002, after mass chemotherapy. The occurrence of B. glabrata in all 11 snail habitats both at and away from water contact sites studied indicates widespread risk of human infection in the study area. In spite of the strong association between B. glabrata and tilapia in fishponds we do not recommend its use in schistosomiasis control for ecological reasons and its relative inefficiency in streams and dams.
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Our objective is to evaluate the habitat preference of freshwater snails in relation to environmental factors and the presence of the competitor snail Melanoides tuberculatus. In the first phase, snails was collected at 12 sites. This sampling sites presented a degree of organic input. In the second phase 33 sampling sites were chosen, covering a variety of lotic and lentic environments. The snail species found at Guapimirim, state of Rio de Janeiro, displayed a marked habitat preference, specially in relation to the physical characteristics of each environment. Other limiting factors for snail distribution at the studied lotic environments were the water current velocity and the amount of organic matter, mainly to Physa marmorata, M. tuberculatus, and Biomphalaria tenagophila. The absence of interactions between M. tuberculatus and another snails could be associated to the distinct spatial distribution of those species and the instability of habitats. This later factor may favor the coexistence of M. tuberculatus with B. glabrata by reduction of population density. In areas of schistosomiasis transmission some habitat modification may add to the instability of the environment, which would make room for the coexistence of M. tuberculatus and Biomphalaria spp. In this way, some of the usual measures for the control of snail hosts would prevent the extinction of populations of Biomphalaria spp. by M. tuberculatus in particular habitats.
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A report on Environmental Inequalities in the UK. Part of the Burden of disease. A clean and healthy environment is a vital component of public health. This is particularly so for children. They are more sensitive to most stressors during development and growth and receive relatively more exposure than adults due to behaviour patterns, lack of awareness, size and biological metabolisms.A study of the contribution of environmental pollutants to the incidence, prevalence, mortality and costs of four categories of paediatric disease in American children estimated total annual costs to be $54.9 billion comprising $43.4 billion for lead poisoning, $2.0 billion for asthma, $0.3 billion for childhood cancer, and $9.2 billion for neurobehavioral disorders; 2.8 % of total U.S. health care costs. As well as childhood conditions, some adult diseases, even those that emerge much later in life, e.g. hypertension, hyperlipidemia, insulin resistance, type 2 diabetes, ischemic heart disease, breast cancer and prostate cancer have some of their origins in utero and childhood. Childhood exposures to environmental health hazards may therefore constitute a source of inequity between generations .