986 resultados para ozone, atmospheric chemistry, air pollution, Mt. Bachelor Observatory.


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The study was designed to investigate the impact of air pollution on monthly inhalation/nebulization procedures in Ribeirao Preto, Sao Paulo State, Brazil, from 2004 to 2010. To assess the relationship between the procedures and particulate matter (PM10) a Bayesian Poisson regression model was used, including a random factor that captured extra-Poisson variability between counts. Particulate matter was associated with the monthly number of inhalation/nebulization procedures, but the inclusion of covariates (temperature, precipitation, and season of the year) suggests a possible confounding effect. Although other studies have linked particulate matter to an increasing number of visits due to respiratory morbidity, the results of this study suggest that such associations should be interpreted with caution.

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Previous studies have shown that particulate matter (PM) compromise birth weight and placental morphology. We hypothesized that exposing mice to ambient PM would affect umbilical cord (UC) morphology. To test this, mice were kept in paired open-top exposure chambers at the same location and ambient conditions but, in one chamber, the air was filtered (F) and, in the other, it was not (NF). UCs were analysed stereologically and by immunohistochemistry to localize isoprostane and endothelin receptors. The cords of mice from NF chambers were smaller in volume due to loss of mucoid connective tissue and decrease in volume of collagen. These structural changes and in umbilical vessels were associated with greater volumes of regions immunostained for isoprostane, ETAR and ETBR. Findings indicate that the adverse effects of PM on birth weight may be mediated in part by alterations in UC structure or imbalances in the endogenous regulators of vascular tone and oxidative stress. (C) 2012 Elsevier Inc. All rights reserved.

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In urban areas of Brazil, vehicle emissions are the principal source of fine particulate matter (PM2.5). The World Health Organization air quality guidelines state that the annual mean concentration of PM2.5 should be below 10 mu g m(-3). In a collaboration of Brazilian institutions, coordinated by the University of Sao Paulo School of Medicine and conducted from June 2007 to August 2008, PM2.5 mass was monitored at sites with high traffic volumes in six Brazilian state capitals. We employed gravimetry to determine PM2.5 mass concentrations, reflectance to quantify black carbon concentrations, X-ray fluorescence to characterize elemental composition, and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM2.5 concentrations and proportions of black carbon (BC) in the cities of Sao Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Recife, and Porto Alegre were 28.1 +/- 13.6 mu g m(-3) (38% BC), 17.2 +/- 11.2 mu g m(-3) (20% BC), 14.7 +/- 7.7 mu g m(-3) (31% BC), 14.4 +/- 9.5 mu g m(-3) (30% BC), 7.3 +/- 3.1 mu g m(-3) (26% BC), and 13.4 +/- 9.9 mu g m(-3) (26% BC), respectively. Sulfur and minerals (Al, Si, Ca, and Fe), derived from fuel combustion and soil resuspension, respectively, were the principal elements of the PM2.5 mass. We discuss the long-term health effects for each metropolitan region in terms of excess mortality risk, which translates to greater health care expenditures. This information could prove useful to decision makers at local environmental agencies.

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The study was designed to investigate the impact of air pollution on monthly inhalation/nebulization procedures in Ribeirão Preto, São Paulo State, Brazil, from 2004 to 2010. To assess the relationship between the procedures and particulate matter (PM10) a Bayesian Poisson regression model was used, including a random factor that captured extra-Poisson variability between counts. Particulate matter was associated with the monthly number of inhalation/nebulization procedures, but the inclusion of covariates (temperature, precipitation, and season of the year) suggests a possible confounding effect. Although other studies have linked particulate matter to an increasing number of visits due to respiratory morbidity, the results of this study suggest that such associations should be interpreted with caution.

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[EN]In this talk we introduce a new methodology for wind field simulation or forecasting over complex terrain. The idea is to use wind measurements or predictions of the HARMONIE mesoscale model as the input data for an adaptive finite element mass consistent wind model [1,2]. The method has been recently implemented in the freely-available Wind3D code [3]. A description of the HARMONIE Non-Hydrostatic Dynamics can be found in [4]. The results of HARMONIE (obtained with a maximum resolution about 1 Km) are refined by the finite element model in a local scale (about a few meters). An interface between both models is implemented such that the initial wind field approximation is obtained by a suitable interpolation of the HARMONIE results…

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The land-atmosphere exchange of atmospheric trace gases is sensitive to meteorological conditions and climate change. It contributes in turn to the atmospheric radiative forcing through its effects on tropospheric chemistry. The interactions between the hydrological cycle and atmospheric processes are intricate and often involve different levels of feedbacks. The Earth system model EMAC is used in this thesis to assess the direct role of the land surface components of the terrestrial hydrological cycle in the emissions, deposition and transport of key trace gases that control tropospheric chemistry. It is also used to examine its indirect role in changing the tropospheric chemical composition through the feedbacks between the atmospheric and the terrestrial branches of the hydrological cycle. Selected features of the hydrological cycle in EMAC are evaluated using observations from different data sources. The interactions between precipitation and the water vapor column, from the atmospheric branch of the hydrological cycle, and evapotranspiration, from its terrestrial branch, are assessed specially for tropical regions. The impacts of changes in the land surface hydrology on surface exchanges and the oxidizing chemistry of the atmosphere are assessed through two sensitivity simulations. In the first, a new parametrization for rainfall interception in the densely vegetated areas in the tropics is implemented, and its effects are assessed. The second study involves the application of a soil moisture forcing that replaces the model calculated soil moisture. Both experiments have a large impact on the local hydrological cycle, dry deposition of soluble and insoluble gases, emissions of isoprene through changes in surface temperature and the Planetary Boundary Layer height. Additionally the soil moisture forcing causes changes in local vertical transport and large-scale circulation. The changes in trace gas exchanges affect the oxidation capacity of the atmosphere through changes in OH, O$_3$, NO$_x$ concentrations.

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Objective: Myocardial infarction has been associated with both transportation noise and air pollution. We examined residential exposure to aircraft noise and mortality from myocardial infarction, taking air pollution into account. Methods: We analyzed the Swiss National Cohort, which includes geocoded information on residence. Exposure to aircraft noise and air pollution was determined based on geospatial noise and air-pollution (PM10) models and distance to major roads. We used Cox proportional hazard models, with age as the timescale. We compared the risk of death across categories of A-weighted sound pressure levels (dB(A)) and by duration of living in exposed corridors, adjusting for PM10 levels, distance to major roads, sex, education, and socioeconomic position of the municipality. Results: We analyzed 4.6 million persons older than 30 years who were followed from near the end of 2000 through December 2005, including 15,532 deaths from myocardial infarction (ICD-10 codes I 21, I 22). Mortality increased with increasing level and duration of aircraft noise. The adjusted hazard ratio comparing ≥60 dB(A) with <45 dB(A) was 1.3 (95% confidence interval = 0.96-1.7) overall, and 1.5 (1.0-2.2) in persons who had lived at the same place for at least 15 years. None of the other endpoints (mortality from all causes, all circulatory disease, cerebrovascular disease, stroke, and lung cancer) was associated with aircraft noise. Conclusion: Aircraft noise was associated with mortality from myocardial infarction, with a dose-response relationship for level and duration of exposure. The association does not appear to be explained by exposure to particulate matter air pollution, education, or socioeconomic status of the municipality.

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Background/Objectives Ambient air pollution can alter cytokine concentrations as shown in vitro and following short-term exposure to high air pollution levels in vivo. Exposure to pollution during late pregnancy has been shown to affect fetal lymphocytic immunophenotypes. However, effects of prenatal exposure to moderate levels of air pollutants on cytokine regulation in cord blood of healthy infants are unknown. Methods In a birth cohort of 265 healthy term-born neonates, we assessed maternal exposure to particles with an aerodynamic diameter of 10 µm or less (PM10), as well as to indoor air pollution during the last trimester, specifically the last 21, 14, 7, 3 and 1 days of pregnancy. As a proxy for traffic-related air pollution, we determined the distance of mothers' homes to major roads. We measured cytokine and chemokine levels (MCP-1, IL-6, IL-10, IL-1ß, TNF-α and GM-CSF) in cord blood serum using LUMINEX technology. Their association with pollution levels was assessed using regression analysis, adjusted for possible confounders. Results Mean (95%-CI) PM10 exposure for the last 7 days of pregnancy was 18.3 (10.3–38.4 µg/m3). PM10 exposure during the last 3 days of pregnancy was significantly associated with reduced IL-10 and during the last 3 months of pregnancy with increased IL-1ß levels in cord blood after adjustment for relevant confounders. Maternal smoking was associated with reduced IL-6 levels. For the other cytokines no association was found. Conclusions Our results suggest that even naturally occurring prenatal exposure to moderate amounts of indoor and outdoor air pollution may lead to changes in cord blood cytokine levels in a population based cohort.

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There is increasing evidence of the adverse impact of prenatal exposure to air pollution. This is of particular interest, as exposure during pregnancy--a crucial time span of important biological development--may have long-term implications. The aims of this review are to show current epidemiological evidence of known effects of prenatal exposure to air pollution and present possible mechanisms behind this process. Harmful effects of exposure to air pollution during pregnancy have been shown for different birth outcomes: higher infant mortality, lower birth weight, impaired lung development, increased later respiratory morbidity, and early alterations in immune development. Although results on lower birth weight are somewhat controversial, evidence for higher infant mortality is consistent in studies published worldwide. Possible mechanisms include direct toxicity of particles due to particle translocation across tissue barriers or particle penetration across cellular membranes. The induction of specific processes or interaction with immune cells in either the pregnant mother or the fetus may be possible consequences. Indirect effects could be oxidative stress and inflammation with consequent hemodynamic alterations resulting in decreased placental blood flow and reduced transfer of nutrients to the fetus. The early developmental phase of pregnancy is thought to be very important in determining long-term growth and overall health. So-called "tracking" of somatic growth and lung function is believed to have a huge impact on long-term morbidity, especially from a public health perspective. This is particularly important in areas with high levels of outdoor pollution, where it is practically impossible for an individual to avoid exposure. Especially in these areas, good evidence for the association between prenatal exposure to air pollution and infant mortality exists, clearly indicating the need for more stringent measures to reduce exposure to air pollution.

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The NMMAPS data package contains daily mortality, air pollution, and weather data originally assembled as part of the National Morbidity,Mortality, and Air Pollution Study (NMMAPS). The data have recently been updated and are available for 108 United States cities for the years 1987--2000. The package provides tools for building versions of the full database in a structured and reproducible manner. These database derivatives may be more suitable for particular analyses. We describe how to use the package to implement a multi-city time series analysis of mortality and PM(10). In addition we demonstrate how to reproduce recent findings based on the NMMAPS data.

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Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.