162 resultados para Environmental Pollutants
Resumo:
In this study, we report the first ever large-scale environmental validation of a microbial reporter-based test to measure arsenic concentrations in natural water resources. A bioluminescence-producing arsenic-inducible bacterium based on Escherichia coli was used as the reporter organism. Specific protocols were developed with the goal to avoid the negative influence of iron in groundwater on arsenic availability to the bioreporter cells. A total of 194 groundwater samples were collected in the Red River and Mekong River Delta regions of Vietnam and were analyzed both by atomic absorption spectroscopy (AAS) and by the arsenic bioreporter protocol. The bacterial cells performed well at and above arsenic concentrations in groundwater of 7 microg/L, with an almost linearly proportional increase of the bioluminescence signal between 10 and 100 microg As/L (r2 = 0.997). Comparisons between AAS and arsenic bioreporter determinations gave an overall average of 8.0% false negative and 2.4% false positive identifications for the bioreporter prediction at the WHO recommended acceptable arsenic concentration of 10 microg/L, which is far betterthan the performance of chemical field test kits. Because of the ease of the measurement protocol and the low application cost, the microbiological arsenic test has a great potential in large screening campaigns in Asia and in other areas suffering from arsenic pollution in groundwater resources.
Resumo:
La pression exercée par les activités humaines menace pratiquement tous les écosystèmes aquatiques du globe. Ainsi, sous l'effet de divers facteurs tels que la pollution, le réchauffement climatique ou encore la pêche industrielle, de nombreuses populations de poissons ont vu leurs effectifs chuter et divers changements morphologiques ont été observés. Dans cette étude, nous nous sommes intéressés à une menace particulière: la sélection induite par la pêche sur la croissance des poissons. En effet, la génétique des populations prédit que la soustraction régulière des individus les plus gros peut entraîner des modifications rapides de certains traits physiques comme la croissance individuelle. Cela a par ailleurs été observé dans de nombreuses populations marines ou lacustres, dont les populations de féras, bondelles et autres corégones des lacs suisses. Toutefois, malgré un nombre croissant d'études décrivant ce phénomène, peu de plans de gestion en tiennent compte, car l'importance des effets génétiques liés à la pêche est le plus souvent négligée par rapport à l'impact des changements environnementaux. Le but premier de cette étude a donc été de quantifier l'importance des facteurs génétiques et environnementaux. Dans le premier chapitre, nous avons étudié la population de palée du lac de Joux (Coregonus palaea). Nous avons déterminé les différentiels de sélection dus à la pêche, c'est-à-dire l'intensité de la sélection sur le taux de croissance, ainsi que les changements nets de croissance au cours du temps. Nous avons observé une baisse marquée de croissance et un différentiel de sélection important indiquant qu'au moins 30% de la diminution de croissance observée était due à la pression de sélection induite par la pêche. Dans le deuxième chapitre, nous avons effectué les mêmes analyses sur deux espèces proches du lac de Brienz (C. albellus et C. fatioi) et avons observé des effets similaires dont l'intensité était spécifique à chaque espèce. Dans le troisième chapitre, nous avons analysé deux autres espèces : C. palaea et C. confusus du lac de Bienne, et avons constaté que le lien entre la pression de sélection et la diminution de croissance était influencé par des facteurs environnementaux. Finalement, dans le dernier chapitre, nous avons étudié les effets potentiels de différentes modifications de la taille des mailles des filets utilisés pour la pêche à l'aide de modèles mathématiques. Nous concluons que la pêche a un effet génétique non négligeable (et donc peu réversible) sur la croissance individuelle dans les populations observée, que cet effet est lié à la compétition pour la nourriture et à la qualité de l'environnement, et que certaines modifications simples de la taille des mailles des filets de pêche pourraient nettement diminuer l'effet de sélection et ainsi ralentir, voir même renverser la diminution de croissance observée.
Resumo:
We have used surface-based electrical resistivity tomography to detect and characterize preferential hydraulic pathways in the immediate downstream area of an abandoned, hazardous landfill. The landfill occupies the void left by a former gravel pit and its base is close to the groundwater table and lacking an engineered barrier. As such, this site is remarkably typical of many small- to medium-sized waste deposits throughout the densely populated and heavily industrialized foreland on both sides of the Alpine arc. Outflows of pollutants lastingly contaminated local drinking water supplies and necessitated a partial remediation in the form of a synthetic cover barrier, which is meant to prevent meteoric water from percolating through the waste before reaching the groundwater table. Any future additional isolation of the landfill in the form of lateral barriers thus requires adequate knowledge of potential preferential hydraulic pathways for outflowing contaminants. Our results, inferred from a suite of tomographically inverted surfaced-based electrical resistivity profiles oriented roughly perpendicular to the local hydraulic gradient, indicate that potential contaminant outflows would predominantly occur along an unexploited lateral extension of the original gravel deposit. This finds its expression as a distinct and laterally continuous high-resistivity anomaly in the resistivity tomograms. This interpretation is ground-truthed through a litholog from a nearby well. Since the probed glacio-fluvial deposits are largely devoid of mineralogical clay, the geometry of hydraulic and electrical pathways across the pore space of a given lithological unit can be assumed to be identical, which allows for an order-of-magnitude estimation of the overall permeability structure. These estimates indicate that the permeability of the imaged extension of the gravel body is at least two to three orders-of-magnitude higher than that of its finer-grained embedding matrix. This corroborates the preeminent role of the high-resistivity anomaly as a potential preferential flow path.
Resumo:
A radiochemical procedure was developed for the sequential determination of Pu and Am radioisotopes in environmental samples. The radioisotope activities were then used to assess the origin and release date of the environmental plutonium. The radioanalytical procedure is based on the separation of Pu and Am on selective extraction chromatographic resins (Eichrom TEVA and DGA). Alpha sources were prepared by electrodeposition on stainless steel discs, and the alpha emitting radionuclides (238Pu, 239,240Pu and 241Am) were measured by alpha spectrometry. For the determination of the beta emitting 241Pu, the Pu alpha source was leached in hot concentrated nitric acid and the Pu fraction further purified by extraction chromatography on a small column of TEVA resin (100 μg of resin in a pipette tip). 241Pu is then measured by ultra low level liquid scintillation counting. Due to the lack of reference material for 241Pu, the proposed radiochemical method was nevertheless validated using four IAEA reference sediments with information values of 241Pu. The proposed method was then used to determine the 238Pu, 239,240Pu, 241Pu and 241Am activity concentrations in alpine soils of France and Switzerland. The soil is the primary receptor of the atmospheric radioactive fallout and, because of the strong binding interaction with soils particles, the isotopes are little fractionated. Therefore, the activity ratios 241Pu/239+240Pu and 238Pu/239,240Pu in soil samples were used to determine the origin (source) and date of the Pu contamination in the investigated alpine sites. The 241Pu/239,240Pu and 238Pu/239,240Pu activity ratios confirmed that the main origin of Pu in the alpine soils was the global fallout from the nuclear bomb tests (NBT) in the fifties and sixties. Furthermore, the 241Pu/241Am activity ratios were used to determine the age of the Pu contamination, which is also an important data for distinguishing the Pu sources. The estimation of the date of the contamination, by the 241Pu/241Am age-dating method, further confirmed the NBT as the Pu source. However, the 241Pu/241Am dating method was limited to samples where Pu-Am fractionation was insignificant. If any, the contribution of the Chernobyl accident in the studied sites is negligible.
Resumo:
The evaluation of radioactivity accidentally released into the atmosphere involves determining the radioactivity levels of rainwater samples. Rainwater scavenges atmospheric airborne radioactivity in such a way that surface contamination can be deduced from rainfall rate and rainwater radioactivity content. For this purpose, rainwater is usually collected in large surface collectors and then measured by gamma-spectrometry after such treatments as evaporation or iron hydroxide precipitation. We found that collectors can be adapted to accept large surface (diameter 47mm) cartridges containing a strongly acidic resin (Dowex AG 88) which is able to quantitatively extract radioactivity from rainwater, even during heavy rainfall. The resin can then be measured by gamma-spectrometry. The detection limit is 0.1Bq per sample of resin (80g) for (137)Cs. Natural (7)Be and (210)Pb can also be measured and the activity ratio of both radionuclides is comparable with those obtained through iron hydroxide precipitation and air filter measurements. Occasionally (22)Na has also been measured above the detection limit. A comparison between the evaporation method and the resin method demonstrated that 2/3 of (7)Be can be lost during the evaporation process. The resin method is simple and highly efficient at extracting radioactivity. Because of these great advantages, we anticipate it could replace former rainwater determination methods. Moreover, it does not necessitate the transportation of large rainwater volumes to the laboratory.
Resumo:
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.
Resumo:
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.
Resumo:
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]
Resumo:
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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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.