971 resultados para Air pollution management


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Prospective cohort studies have provided evidence on longer-term mortality risks of fine particulate matter (PM2.5), but due to their complexity and costs, only a few have been conducted. By linking monitoring data to the U.S. Medicare system by county of residence, we developed a retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), comprising over 20 million enrollees in the 250 largest counties during 2000-2002. We estimated log-linear regression models having as outcome the age-specific mortality rate for each county and as the main predictor, the average level for the study period 2000. Area-level covariates were used to adjust for socio-economic status and smoking. We reported results under several degrees of adjustment for spatial confounding and with stratification into by eastern, central and western counties. We estimated that a 10 µg/m3 increase in PM25 is associated with a 7.6% increase in mortality (95% CI: 4.4 to 10.8%). We found a stronger association in the eastern counties than nationally, with no evidence of an association in western counties. When adjusted for spatial confounding, the estimated log-relative risks drop by 50%. We demonstrated the feasibility of using Medicare data to establish cohorts for follow-up for effects of air pollution. Particulate matter (PM) air pollution is a global public health problem (1). In developing countries, levels of airborne particles still reach concentrations at which serious health consequences are well-documented; in developed countries, recent epidemiologic evidence shows continued adverse effects, even though particle levels have declined in the last two decades (2-6). Increased mortality associated with higher levels of PM air pollution has been of particular concern, giving an imperative for stronger protective regulations (7). Evidence on PM and health comes from studies of acute and chronic adverse effects (6). The London Fog of 1952 provides dramatic evidence of the unacceptable short-term risk of extremely high levels of PM air pollution (8-10); multi-site time-series studies of daily mortality show that far lower levels of particles are still associated with short-term risk (5)(11-13). Cohort studies provide complementary evidence on the longer-term risks of PM air pollution, indicating the extent to which exposure reduces life expectancy. The design of these studies involves follow-up of cohorts for mortality over periods of years to decades and an assessment of mortality risk in association with estimated long-term exposure to air pollution (2-4;14-17). Because of the complexity and costs of such studies, only a small number have been conducted. The most rigorously executed, including the Harvard Six Cities Study and the American Cancer Society’s (ACS) Cancer Prevention Study II, have provided generally consistent evidence for an association of long- term exposure to particulate matter air pollution with increased all-cause and cardio-respiratory mortality (2,4,14,15). Results from these studies have been used in risk assessments conducted for setting the U.S. National Ambient Air Quality Standard (NAAQS) for PM and for estimating the global burden of disease attributable to air pollution (18,19). Additional prospective cohort studies are necessary, however, to confirm associations between long-term exposure to PM and mortality, to broaden the populations studied, and to refine estimates by regions across which particle composition varies. Toward this end, we have used data from the U.S. Medicare system, which covers nearly all persons 65 years of age and older in the United States. We linked Medicare mortality data to (particulate matter less than 2.5 µm in aerodynamic diameter) air pollution monitoring data to create a new retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), consisting of 20 million persons from 250 counties and representing about 50% of the US population of elderly living in urban settings. In this paper, we report on the relationship between longer-term exposure to PM2.5 and mortality risk over the period 2000 to 2002 in the MCAPS.

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Post-natal exposure to air pollution is associated with diminished lung growth during school age. The current authors aimed to determine whether pre-natal exposure to air pollution is associated with lung function changes in the newborn. In a prospective birth cohort of 241 healthy term-born neonates, tidal breathing, lung volume, ventilation inhomogeneity and exhaled nitric oxide (eNO) were measured during unsedated sleep at age 5 weeks. Maternal exposure to particles with a 50% cut-off aerodynamic diameter of 10 microm (PM(10)), nitrogen dioxide (NO(2)) and ozone (O(3)), and distance to major roads were estimated during pregnancy. The association between these exposures and lung function was assessed using linear regression. Minute ventilation was higher in infants with higher pre-natal PM(10) exposure (24.9 mL x min(-1) per microg x m(-3) PM(10)). The eNO was increased in infants with higher pre-natal NO(2) exposure (0.98 ppb per microg x m(-3) NO(2)). Post-natal exposure to air pollution did not modify these findings. No association was found for pre-natal exposure to O(3) and lung function parameters. The present results suggest that pre-natal exposure to air pollution might be associated with higher respiratory need and airway inflammation in newborns. Such alterations during early lung development may be important regarding long-term respiratory morbidity.

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Climate change alone influences future levels of tropospheric ozone and their precursors through modifications of gas-phase chemistry, transport, removal, and natural emissions. The goal of this study is to determine at what extent the modes of variability of gas-phase pollutants respond to different climate change scenarios over Europe. The methodology includes the use of the regional modeling system MM5 (regional climate model version)-CHIMERE for a target domain covering Europe. Two full-transient simulations covering from 1991–2050 under the SRES A2 and B2 scenarios driven by ECHO-G global circulation model have been compared. The results indicate that the spatial patterns of variability for tropospheric ozone are similar for both scenarios, but the magnitude of the change signal significantly differs for A2 and B2. The 1991–2050 simulations share common characteristics for their chemical behavior. As observed from the NO2 and α-pinene modes of variability, our simulations suggest that the enhanced ozone chemical activity is driven by a number of parameters, such as the warming-induced increase in biogenic emissions and, to a lesser extent, by the variation in nitrogen dioxide levels. For gas-phase pollutants, the general increasing trend for ozone found under A2 and B2 forcing is due to a multiplicity of climate factors, such as increased temperature, decreased wet removal associated with an overall decrease of precipitation in southern Europe, increased photolysis of primary and secondary pollutants as a consequence of lower cloudiness and increased biogenic emissions fueled by higher temperatures.

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Exposure to outdoor air pollutants and passive tobacco smoke are common but avoidable worldwide risk factors for morbidity and mortality of individuals. In addition to well-known effects of pollutants on the cardiovascular system and the development of cancer, in recent years the association between air pollution and respiratory morbidity has become increasingly apparent. Not only in adults, but also in children with asthma and in healthy children a clear harmful effect of exposure towards air pollutants has been demonstrated in many studies. Among others increased pollution has been shown to result in more frequent and more severe respiratory symptoms, more frequent exacerbations, higher need for asthma medication, poorer lung function and increased visits to the emergency department and more frequent hospitalisations. While these associations are well established, the available data on the role of air pollution in the development of asthma seems less clear. Some studies have shown that increased exposure towards tobacco smoke and air pollution leads to an increase in asthma incidence and prevalence; others were not able to confirm those findings. Possible reasons for this discrepancy are different definitions of the outcome asthma, different methods for exposure estimation and differences in the populations studied with differing underlying genetic backgrounds. Regardless of this inconsistency, several mechanisms have already been identified linking air pollution with asthma development. Among these are impaired lung growth and development, immunological changes, genetic or epigenetic effects or increased predisposition for allergic sensitisation. What the exact interactions are and which asthmatic phenotypes will be influenced most by pollutants will be shown by future studies. This knowledge will then be helpful in exploring possible preventive measures for the individual and to help policy makers in deciding upon most appropriate regulations on a population level.

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Many studies have shown relationships between air pollution and the rate of hospital admissions for asthma. A few studies have controlled for age-specific effects by adding separate smoothing functions for each age group. However, it has not yet been reported whether air pollution effects are significantly different for different age groups. This lack of information is the motivation for this study, which tests the hypothesis that air pollution effects on asthmatic hospital admissions are significantly different by age groups. Each air pollutant's effect on asthmatic hospital admissions by age groups was estimated separately. In this study, daily time-series data for hospital admission rates from seven cities in Korea from June 1999 through 2003 were analyzed. The outcome variable, daily hospital admission rates for asthma, was related to five air pollutants which were used as the independent variables, namely particulate matter <10 micrometers (μm) in aerodynamic diameter (PM10), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Meteorological variables were considered as confounders. Admission data were divided into three age groups: children (<15 years of age), adults (ages 15-64), and elderly (≥ 65 years of age). The adult age group was considered to be the reference group for each city. In order to estimate age-specific air pollution effects, the analysis was separated into two stages. In the first stage, Generalized Additive Models (GAMs) with cubic spline for smoothing were applied to estimate the age-city-specific air pollution effects on asthmatic hospital admission rates by city and age group. In the second stage, the Bayesian Hierarchical Model with non-informative prior which has large variance was used to combine city-specific effects by age groups. The hypothesis test showed that the effects of PM10, CO and NO2 were significantly different by age groups. Assuming that the air pollution effect for adults is zero as a reference, age-specific air pollution effects were: -0.00154 (95% confidence interval(CI)= (-0.0030,-0.0001)) for children and 0.00126 (95% CI = (0.0006, 0.0019)) for the elderly for PM 10; -0.0195 (95% CI = (-0.0386,-0.0004)) for children for CO; and 0.00494 (95% CI = (0.0028, 0.0071)) for the elderly for NO2. Relative rates (RRs) were 1.008 (95% CI = (1.000-1.017)) in adults and 1.021 (95% CI = (1.012-1.030)) in the elderly for every 10 μg/m3 increase of PM10 , 1.019 (95% CI = (1.005-1.033)) in adults and 1.022 (95% CI = (1.012-1.033)) in the elderly for every 0.1 part per million (ppm) increase of CO; 1.006 (95%CI = (1.002-1.009)) and 1.019 (95%CI = (1.007-1.032)) in the elderly for every 1 part per billion (ppb) increase of NO2 and SO2, respectively. Asthma hospital admissions were significantly increased for PM10 and CO in adults, and for PM10, CO, NO2 and SO2 in the elderly.^

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An investigation was undertaken to determine the chemical characterization of inhalable particulate matter in the Houston area, with special emphasis on source identification and apportionment of outdoor and indoor atmospheric aerosols using multivariate statistical analyses.^ Fine (<2.5 (mu)m) particle aerosol samples were collected by means of dichotomous samplers at two fixed site (Clear Lake and Sunnyside) ambient monitoring stations and one mobile monitoring van in the Houston area during June-October 1981 as part of the Houston Asthma Study. The mobile van allowed particulate sampling to take place both inside and outside of twelve homes.^ The samples collected for 12-h sampling on a 7 AM-7 PM and 7 PM-7 AM (CDT) schedule were analyzed for mass, trace elements, and two anions. Mass was determined gravimetrically. An energy-dispersive X-ray fluorescence (XRF) spectrometer was used for determination of elemental composition. Ion chromatography (IC) was used to determine sulfate and nitrate.^ Average chemical compositions of fine aerosol at each site were presented. Sulfate was found to be the largest single component in the fine fraction mass, comprising approximately 30% of the fine mass outdoors and 12% indoors, respectively.^ Principal components analysis (PCA) was applied to identify sources of aerosols and to assess the role of meteorological factors on the variation in particulate samples. The results suggested that meteorological parameters were not associated with sources of aerosol samples collected at these Houston sites.^ Source factor contributions to fine mass were calculated using a combination of PCA and stepwise multivariate regression analysis. It was found that much of the total fine mass was apparently contributed by sulfate-related aerosols. The average contributions to the fine mass coming from the sulfate-related aerosols were 56% of the Houston outdoor ambient fine particulate matter and 26% of the indoor fine particulate matter.^ Characterization of indoor aerosol in residential environments was compared with the results for outdoor aerosols. It was suggested that much of the indoor aerosol may be due to outdoor sources, but there may be important contributions from common indoor sources in the home environment such as smoking and gas cooking. ^

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The association between fine particulate matter air pollution (PM2.5) and cardiovascular disease (CVD) mortality was spatially analyzed for Harris County, Texas, at the census tract level. The objective was to assess how increased PM2.5 exposure related to CVD mortality in this area while controlling for race, income, education, and age. An estimated exposure raster was created for Harris County using Kriging to estimate the PM2.5 exposure at the census tract level. The PM2.5 exposure and the CVD mortality rates were analyzed in an Ordinary Least Squares (OLS) regression model and the residuals were subsequently assessed for spatial autocorrelation. Race, median household income, and age were all found to be significant (p<0.05) predictors in the model. This study found that for every one μg/m3 increase in PM2.5 exposure, holding age and education variables constant, an increase of 16.57 CVD deaths per 100,000 would be predicted for increased minimum exposure values and an increase of 14.47 CVD deaths per 100,000 would be predicted for increased maximum exposure values. This finding supports previous studies associating PM2.5 exposure with CVD mortality. This study further identified the areas of greatest PM2.5 exposure in Harris County as being the geographical locations of populations with the highest risk of CVD (i.e., predominantly older, low-income populations with a predominance of African Americans). The magnitude of the effect of PM2.5 exposure on CVD mortality rates in the study region indicates a need for further community-level studies in Harris County, and suggests that reducing excess PM2.5 exposure would reduce CVD mortality.^

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In the early stages of the development of Japan’s environmental policy, sulfur oxide (SOx) emissions, which seriously damage health, was the most important air pollution problem. In the second half of the 1960s and the first half of the 1970s, the measures against SOx emissions progressed quickly, and these emissions were reduced drastically. The most important factor of the reduction was the conversion to a low-sulfur fuel for large-scale fuel users, such as the electric power industry. However, industries started conversion to low-sulfur fuel not due to environmental concerns, but simply to reduce costs. Furthermore, the interaction among the various interests of the electric power industry, oil refineries, the central government, local governments, and citizens over the energy and environmental policies led to the measures against SOx emissions by fuel conversion.

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As it is defined in ATM 2000+ Strategy (Eurocontrol 2001), the mission of the Air Traffic Management (ATM) System is: “For all the phases of a flight, the ATM system should facilitate a safe, efficient, and expedite traffic flow, through the provision of adaptable ATM services that can be dimensioned in relation to the requirements of all the users and areas of the European air space. The ATM services should comply with the demand, be compatible, operate under uniform principles, respect the environment and satisfy the national security requirements.” The objective of this paper is to present a methodology designed to evaluate the status of the ATM system in terms of the relationship between the offered capacity and traffic demand, identifying weakness areas and proposing solutions. The first part of the methodology relates to the characterization and evaluation of the current system, while a second part proposes an approach to analyze the possible development limit. As part of the work, general criteria are established to define the framework in which the analysis and diagnostic methodology presented is placed. They are: the use of Air Traffic Control (ATC) sectors as analysis unit, the presence of network effects, the tactical focus, the relative character of the analysis, objectivity and a high level assessment that allows assumptions on the human and Communications, Navigation and Surveillance (CNS) elements, considered as the typical high density air traffic resources. The steps followed by the methodology start with the definition of indicators and metrics, like the nominal criticality or the nominal efficiency of a sector; scenario characterization where the necessary data is collected; network effects analysis to study the relations among the constitutive elements of the ATC system; diagnostic by means of the “System Status Diagram”; analytical study of the ATC system development limit; and finally, formulation of conclusions and proposal for improvement. This methodology was employed by Aena (Spanish Airports Manager and Air Navigation Service Provider) and INECO (Spanish Transport Engineering Company) in the analysis of the Spanish ATM System in the frame of the Spanish airspace capacity sustainability program, although it could be applied elsewhere.

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First, this paper describes a future layered Air Traffic Management (ATM) system centred in the execution phase of flights. The layered ATM model is based on the work currently performed by SESAR [1] and takes into account the availability of accurate and updated flight information ?seen by all? across the European airspace. This shared information of each flight will be referred as Reference Business Trajectory (RBT). In the layered ATM system, exchanges of information will involve several actors (human or automatic), which will have varying time horizons, areas of responsibility and tasks. Second, the paper will identify the need to define the negotiation processes required to agree revisions to the RBT in the layered ATM system. Third, the final objective of the paper is to bring to the attention of researchers and engineers the communalities between multi-player games and Collaborative Decision Making processes (CDM) in a layered ATM system

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Ponencia invitada sobre gestion de trafico aereo en el curso de verano de la UPM Research in Decision Support Systems for future Air Traffic Management

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The Spanish NGO "Alianza por la Solidaridad" has installed improved cookstoves in 3000 households during 2012 and 2013 to improve energy efficiency reducing fuelwood consumption and to improve in-door air quality. The type of cookstoves were Noflaye Jeeg and Noflaye Jaboot and were installed in the Cassamance Natural Subregion covering part of Senegal, The Gambia and Guinea-Bissau. The Technical University of Madrid (UPM) has conducted a field study on a sample of these households to assess the effect of improved cookstoves on kitchen air quality. Measurements of carbon monoxide (CO) and fine particle matter (PM2.5) were taken for 24-hr period before and after the installation of improved cook-stoves. The 24-hr mean CO concentrations were lower than the World Health Organization (WHO) guidelines for Guinea-Bissau but higher for Senegal and Gambia, even after the installation of improved cookstoves. As for PM2.5 concentrations, 24-hr mean were always higher than these guidelines. However, improved cookstoves produced significant reductions on 24-hr mean CO and PM2.5 concentrations in Senegal and for mean and maximum PM2.5 concentration on Gambia. Although this variability needs to be explained by further research to determine which other factors could affect indoor air pollution, the study provided a better understanding of the problem and envisaged alternatives to be implemented in fu-ture phases of the NGO project.

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The SESAR (Single European Sky ATM Research) program is an ambitious re-search and development initiative to design the future European air traffic man-agement (ATM) system. The study of the behavior of ATM systems using agent-based modeling and simulation tools can help the development of new methods to improve their performance. This paper presents an overview of existing agent-based approaches in air transportation (paying special attention to the challenges that exist for the design of future ATM systems) and, subsequently, describes a new agent-based approach that we proposed in the CASSIOPEIA project, which was developed according to the goals of the SESAR program. In our approach, we use agent models for different ATM stakeholders, and, in contrast to previous work, our solution models new collaborative decision processes for flow traffic management, it uses an intermediate level of abstraction (useful for simulations at larger scales), and was designed to be a practical tool (open and reusable) for the development of different ATM studies. It was successfully applied in three stud-ies related to the design of future ATM systems in Europe.