57 resultados para Ciclismo indoor

em Université de Lausanne, Switzerland


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Introduction: Exposure to environmental tobacco smoke (ETS) is a major environmental risk factor. Indoor contaminants come from a variety of sources, which can include inadequate ventilation, volatile organic compounds (VOCs), biological agents, combustion products, and ETS. Because ETS is one of the most frequent causes of IAQ complaints as well as the high mortality of passive smoking, in June 2004 the University of Geneva made the decision to ban smoking inside the so called "Uni-Mail" building, the biggest Swiss University human science building of recent construction, and the ordinance was applied beginning in October 2004. This report presents the finding related to the IAQ of the "Uni-Mail" building before and after smoking bans using nicotine, suspended dust, condensate and PAHs level in air as tracers to perform an assessment of passive tobacco exposure for non-smokers inside the building. Methods: Respirable particles (RSP) A real time aerosol monitor (model DataRAM)was place at sampling post 1, level ground floor. Condensate It consists in extracting any organic matter taken on the glass fibre filters by MeOH, and then measuring the total absorbent of the MeOH extract to the UV wavelength of 447 nm. Nicotine Nicotine was taken by means of cartridges containing of XAD-4 to the fixed flow of 0.5 L/min. The analytical method used for the determination of nicotine is based on gas chromatography with Nitrogen selective detector GC-NPD. Results: Figure 1 shows the box plot density display of 3 parameters before and after smoking bans for all 7 sampling posts: dust, condensate and nicotine in air in μg/m3. Conclusion: Before the smoking ban, the level of the concentrations of respirable particles (RSP) is raised more, average of the day 320 μg/m3, with peaks of more than 1000 μg/m3, compared with the values of the surrounding air between 22 and 30 μg/m3. The nicotine level is definitely more important (average 5.53 μg/m3, field 1.5 to 17.9 μg/m3). Once the smoking bans inside the building were applied, one notes a clear improvement in terms of concentrations of pollutants. For dust, the concentration fell by 3 times (average: 130 μg/m3, range: 40 to 160 μg/m3) and that of nicotine by 10 times (average: 0.53 μg/m3, range: 0 to 1.69 μg/m3) compared to that found before smoking bans. The outdoor air RSP concentration was 22 μg/m3 or 10 times lower. Nicotine seems to be the best tracer for ETS free of interference, independent of location or season.

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PURPOSE: In Switzerland, nationwide large-scale radon surveys have been conducted since the early 1980s to establish the distribution of indoor radon concentrations (IRC). The aim of this work was to study the factors influencing IRC in Switzerland using univariate analyses that take into account biases caused by spatial irregularities of sampling. METHODS: About 212,000 IRC measurements carried out in more than 136,000 dwellings were available for this study. A probability map to assess risk of exceeding an IRC of 300 Bq/m(3) was produced using basic geostatistical techniques. Univariate analyses of IRC for different variables, namely the type of radon detector, various building characteristics such as foundation type, year of construction and building type, as well as the altitude, the average outdoor temperature during measurement and the lithology, were performed comparing 95% confidence intervals among classes of each variable. Furthermore, a map showing the spatial aggregation of the number of measurements was generated for each class of variable in order to assess biases due to spatially irregular sampling. RESULTS: IRC measurements carried out with electret detectors were 35% higher than measurements performed with track detectors. Regarding building characteristics, the IRC of apartments are significantly lower than individual houses. Furthermore, buildings with concrete foundations have the lowest IRC. A significant decrease in IRC was found in buildings constructed after 1900 and again after 1970. Moreover, IRC decreases at higher outdoor temperatures. There is also a tendency to have higher IRC with altitude. Regarding lithology, carbonate rock in the Jura Mountains produces significantly higher IRC, almost by a factor of 2, than carbonate rock in the Alps. Sedimentary rock and sediment produce the lowest IRC while carbonate rock from the Jura Mountains and igneous rock produce the highest IRC. Potential biases due to spatially unbalanced sampling of measurements were identified for several influencing factors. CONCLUSIONS: Significant associations were found between IRC and all variables under study. However, we showed that the spatial distribution of samples strongly affected the relevance of those associations. Therefore, future methods to estimate local radon hazards should take the multidimensionality of the process of IRC into account.

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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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Neglecting health effects from indoor pollutant emissions and exposure, as currently done in Life Cycle Assessment (LCA), may result in product or process optimizations at the expense of workers' or consumers' health. To close this gap, methods for considering indoor exposure to chemicals are needed to complement the methods for outdoor human exposure assessment already in use. This paper summarizes the work of an international expert group on the integration of human indoor and outdoor exposure in LCA, within the UNEP/ SETAC Life Cycle Initiative. A new methodological framework is proposed for a general procedure to include human-health effects from indoor exposure in LCA. Exposure models from occupational hygiene and household indoor air quality studies and practices are critically reviewed and recommendations are provided on the appropriateness of various model alternatives in the context of LCA. A single-compartment box model is recommended for use as a default in LCA, enabling one to screen occupational and household exposures consistent with the existing models to assess outdoor emission in a multimedia environment. An initial set of model parameter values was collected. The comparison between indoor and outdoor human exposure per unit of emission shows that for many pollutants, intake per unit of indoor emission may be several orders of magnitude higher than for outdoor emissions. It is concluded that indoor exposure should be routinely addressed within LCA.

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In European countries and North America, people spend 80 to 90% of time inside buildings and thus breathe indoor air. In Switzerland, special attention has been devoted to the 16 stations of the national network of observation of atmospheric pollutants (NABEL). The results indicate a reduction in outdoor pollution over the last ten years. With such a decrease in pollution over these ten years the question becomes: how can we explain an increase of diseases? Indoor pollution can be the cause. Indoor contaminants that may create indoor air quality (IAQ) problems come from a variety of sources. These can include inadequate ventilation, temperature and humidity dysfunction, and volatile organic compounds (VOCs). The health effects from these contaminants are varied and can range from discomfort, irritation and respiratory diseases to cancer. Among such contaminants, environmental tobacco smoke (ETS) could be considered the most important in terms of both health effects and engineering controls of ventilation. To perform indoor pollution monitoring, several selected ETS tracers can be used including carbon monoxide (CO), carbon dioxide (CO2), respirable particles (RSP), condensate, nicotine, polycyclic aromatic hydrocarbons (PAHs), nitrosamines, etc. In this paper, some examples are presented of IAQ problems that have occurred following the renewal of buildings and energy saving concerns. Using industrial hygiene sampling techniques and focussing on selected priority pollutants used as tracers, various problems have been identified and solutions proposed. [Author]

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A majority of smokers and non-smokers mind tobacco smoke. Passive smoking causes death by sudden infant death, lung cancer and coronary heart disease. 3000 to 6000 persons are killed every year in France. The lack of implementation of the Evin's law published in 1991 explains why non-smokers are not given the protection they can expect. The trend of scientific knowledge and of French and international public opinions support a growing demand for a complete protection of non-smokers with a total ban of smoking in all public or working places.

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The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.