968 resultados para mercury pollution


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Untreated wastewater being directly discharged into rivers is a very harmful environmental hazard that needs to be tackled urgently in many countries. In order to safeguard the river ecosystem and reduce water pollution, it is important to have an effluent charge policy that promotes the investment of wastewater treatment technology by domestic firms. This paper considers the strategic interaction between the government and the domestic firms regarding the investment in the wastewater treatment technology and the design of optimal e­ffluent charge policy that should be implemented. In this model, the higher is the proportion of non-investing firms, the higher would be the probability of having to incur an e­ffluent charge and the higher would be that charge. On one hand the government needs to impose a sufficiently strict policy to ensure that firms have strong incentive to invest. On the other hand, it cannot be too strict that it drives out firms which cannot afford to invest in such expensive technology. The paper analyses the factors that affect the probability of investment in this technology. It also explains the difficulty of imposing a strict environment policy in countries that have too many small firms which cannot afford to invest unless subsidised.

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This study shows the efficiency of passive sampling to reveal industrial and agricultural pollution trends. Two practical applications for nonpolar and polar contaminants are presented. Low-density polyethylene (LDPE) samplers were deployed for one year in the Venoge River (VD) to monitor indicator PCBs (iPCBs, IUPAC nos. 28, 52, 101, 138, 153 and 180). The results showed that the impact of PCB emissions into the river is higher in summer than in other seasons due to the low flow rate of the river during this period. P,olar organic chemical integrative samplers (POCIS) were deployed for 4 months in the Sion-Riddes canal (VS) to investigate herbicides (terbuthylazine, diuron and linuron). Desisopropylatrazine-d5 (DIA-d5) was tested as a performance reference compound (PRC) to estimate aqueous concentration. The results showed an increase of water contamination due to the studied agricultural area. The maximal contamination was observed in April and corresponds to the period of herbicide application on the crops.

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PURPOSE: In Burkina Faso, gold ore is one of the main sources of income for an important part of the active population. Artisan gold miners use mercury in the extraction, a toxic metal whose human health risks are well known. The aim of the present study was to assess mercury exposure as well as to understand the exposure determinants of gold miners in Burkinabe small-scale mines.METHODS: The examined gold miners' population on the different selected gold mining sites was composed by persons who were directly and indirectly related to gold mining activities. But measurement of urinary mercury was performed on workers most susceptible to be exposed to mercury. Thus, occupational exposure to mercury was evaluated among ninety-three workers belonging to eight different gold mining sites spread in six regions of Burkina Faso. Among others, work-related exposure determinants were taken into account for each person during urine sampling as for example amalgamating or heating mercury. All participants were medically examined by a local medical team in order to identify possible symptoms related to the toxic effect of mercury.RESULTS: Mercury levels were high, showing that 69% of the measurements exceeded the ACGIH (American Conference of Industrial Hygienists) biological exposure indice (BEI) of 35 µg per g of creatinine (µg/g-Cr) (prior to shift) while 16% even exceeded 350 µg/g-Cr. Basically, unspecific but also specific symptoms related to mercury toxicity could be underlined among the persons who were directly related to gold mining activities. Only one-third among the studied subpopulation reported about less than three symptoms possibly associated to mercury exposure and nearly half of them suffered from at least five of these symptoms. Ore washers were more involved in the direct handling of mercury while gold dealers in the final gold recovery activities. These differences may explain the overexposure observed in gold dealers and indicate that the refining process is the major source of exposure.CONCLUSIONS: This study attests that mercury exposure still is an issue of concern. North-South collaborations should encourage knowledge exchange between developing and developed countries, for a cleaner artisanal gold mining process and thus for reducing human health and environmental hazards due to mercury use.

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Soil transmitted helminth (STH) infection are endemic in developing countries. A study was carried out of sewage farms, streams and vegetables to determine the sources and routes of STH infection in Sanliurfa, Turkey. Stool samples from farmhouse inhabitants as well as soil and vegetable samples from the gardens were collected and examined. In addition, water samples from streams and vegetable samples from the city market were collected and examined. One hundred and eighty-seven (59.5%) of a total of 314 samples, including 88.4% of the stool samples, 60.8% of the water samples, 84.4% of the soil samples and 14% of the vegetable samples, were found to be positive for STH eggs. These results indicate that the water, soil and vegetables are heavily contaminated, and suggest a vicious circle between humans and the environment. Improving environmental sanitation is imperative for the control of soil-transmitted helminthiasis in Sanliurfa.

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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 increase in mortality risk associated with long-term exposure to particulate air pollution is one of the most important, and best-characterised, effects of air pollution on health. This report presents estimates of the size of this effect on mortality in local authority areas in the UK, building upon the attributable fractions reported as an indicator in the public health outcomes framework for England. It discusses the concepts and assumptions underlying these calculations and gives information on how such estimates can be made. The estimates are expected to be useful to health and wellbeing boards when assessing local public health priorities, as well as to others working in the field of air quality and public health. The estimates of mortality burden are based on modelled annual average concentrations of fine particulate matter (PM2.5) in each local authority area originating from human activities. Local data on the adult population and adult mortality rates is also used. Central estimates of the fraction of mortality attributable to long-term exposure to current levels of anthropogenic (human-made) particulate air pollution range from around 2.5% in some local authorities in rural areas of Scotland and Northern Ireland and between 3 and 5% in Wales, to over 8% in some London boroughs. Because of uncertainty in the increase in mortality risk associated with ambient PM2.5, the actual burdens associated with these modelled concentrations could range from approximately one-sixth to about double these figures. Thus, current levels of particulate air pollution have a considerable impact on public health. Measures to reduce levels of particulate air pollution, or to reduce exposure of the population to such pollution, are regarded as an important public health initiative.

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Industrial pollution due to heavy metals such as mercury is a major concern for the environment and public health. Mercury, in particular methylmercury (MeHg), primarily affects brain development and neuronal activity, resulting in neurotoxic effects. Because chemokines can modulate brain functions and are involved in neuroinflammatory and neurodegenerative diseases, we tested the possibility that the neurotoxic effect of MeHg may interfere with the chemokine CCL2. We have used an original protocol in young mice using a MeHg-contaminated fish-based diet for 3 months relevant to human MeHg contamination. We observed that MeHg induced in the mice cortex a decrease in CCL2 concentrations, neuronal cell death, and microglial activation. Knock-out (KO) CCL2 mice fed with a vegetal control food already presented a decrease in cortical neuronal cell density in comparison with wild-type animals under similar diet conditions, suggesting that the presence of CCL2 is required for normal neuronal survival. Moreover, KO CCL2 mice showed a pronounced neuronal cell death in response to MeHg. Using in vitro experiments on pure rat cortical neurons in culture, we observed by blockade of the CCL2/CCR2 neurotransmission an increased neuronal cell death in response to MeHg neurotoxicity. Furthermore, we showed that sod genes are upregulated in brain of wild-type mice fed with MeHg in contrast to KO CCL2 mice and that CCL2 can blunt in vitro the decrease in glutathione levels induced by MeHg. These original findings demonstrate that CCL2 may act as a neuroprotective alarm system in brain deficits due to MeHg intoxication.

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Background Maternal exposure to air pollution has been related to fetal growth in a number of recent scientific studies. The objective of this study was to assess the association between exposure to air pollution during pregnancy and anthropometric measures at birth in a cohort in Valencia, Spain. Methods Seven hundred and eighty-five pregnant women and their singleton newborns participated in the study. Exposure to ambient nitrogen dioxide (NO2) was estimated by means of land use regression. NO2 spatial estimations were adjusted to correspond to relevant pregnancy periods (whole pregnancy and trimesters) for each woman. Outcome variables were birth weight, length, and head circumference (HC), along with being small for gestational age (SGA). The association between exposure to residential outdoor NO2 and outcomes was assessed controlling for potential confounders and examining the shape of the relationship using generalized additive models (GAM). Results For continuous anthropometric measures, GAM indicated a change in slope at NO2 concentrations of around 40 μg/m3. NO2 exposure >40 μg/m3 during the first trimester was associated with a change in birth length of -0.27 cm (95% CI: -0.51 to -0.03) and with a change in birth weight of -40.3 grams (-96.3 to 15.6); the same exposure throughout the whole pregnancy was associated with a change in birth HC of -0.17 cm (-0.34 to -0.003). The shape of the relation was seen to be roughly linear for the risk of being SGA. A 10 μg/m3 increase in NO2 during the second trimester was associated with being SGA-weight, odds ratio (OR): 1.37 (1.01-1.85). For SGA-length the estimate for the same comparison was OR: 1.42 (0.89-2.25). Conclusions Prenatal exposure to traffic-related air pollution may reduce fetal growth. Findings from this study provide further evidence of the need for developing strategies to reduce air pollution in order to prevent risks to fetal health and development.

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BACKGROUND. A growing body of research suggests that prenatal exposure to air pollution may be harmful to fetal development. We assessed the association between exposure to air pollution during pregnancy and anthropometric measures at birth in four areas within the Spanish Children's Health and Environment (INMA) mother and child cohort study. METHODS. Exposure to ambient nitrogen dioxide (NO2) and benzene was estimated for the residence of each woman (n = 2,337) for each trimester and for the entire pregnancy. Outcomes included birth weight, length, and head circumference. The association between residential outdoor air pollution exposure and birth outcomes was assessed with linear regression models controlled for potential confounders. We also performed sensitivity analyses for the subset of women who spent more time at home during pregnancy. Finally, we performed a combined analysis with meta-analysis techniques. RESULTS. In the combined analysis, an increase of 10 µg/m3 in NO2 exposure during pregnancy was associated with a decrease in birth length of -0.9 mm [95% confidence interval (CI), -1.8 to -0.1 mm]. For the subset of women who spent ≥ 15 hr/day at home, the association was stronger (-0.16 mm; 95% CI, -0.27 to -0.04). For this same subset of women, a reduction of 22 g in birth weight was associated with each 10-µg/m3 increase in NO2 exposure in the second trimester (95% CI, -45.3 to 1.9). We observed no significant relationship between benzene levels and birth outcomes. CONCLUSIONS. NO2 exposure was associated with reductions in both length and weight at birth. This association was clearer for the subset of women who spent more time at home.

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Some years ago, a parish in Geneva decided to reduce heating costs by insulating its church to make it more energy efficient. Three years after the last renovations, it was observed that the internal surfaces of the naves had already become dusty compared with the customary frequency of 10-12 years. Dust even deposited on various surfaces during religious services. Our investigation showed that nearly all the dust found inside the church may in fact be soot from incense and candle combustion. Incense appears to be a significant source of polycyclic aromatic hydrocarbons. With a mechanical ventilation system and petrol lamps resembling candles the problem can be resolved.

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It can be assumed that the composition of Mercury’s thin gas envelope (exosphere) is related to thecomposition of the planets crustal materials. If this relationship is true, then inferences regarding the bulkchemistry of the planet might be made from a thorough exospheric study. The most vexing of allunsolved problems is the uncertainty in the source of each component. Historically, it has been believedthat H and He come primarily from the solar wind, while Na and K originate from volatilized materialspartitioned between Mercury’s crust and meteoritic impactors. The processes that eject atoms andmolecules into the exosphere of Mercury are generally considered to be thermal vaporization, photonstimulateddesorption (PSD), impact vaporization, and ion sputtering. Each of these processes has its owntemporal and spatial dependence. The exosphere is strongly influenced by Mercury’s highly ellipticalorbit and rapid orbital speed. As a consequence the surface undergoes large fluctuations in temperatureand experiences differences of insolation with longitude. We will discuss these processes but focus moreon the expected surface composition and solar wind particle sputtering which releases material like Caand other elements from the surface minerals and discuss the relevance of composition modelling