914 resultados para air pollution index
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Mode of access: Internet.
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This study analyzes the management of air pollutant substance in Chinese industrial sectors from 1998 to 2009. Decomposition analysis applying the logarithmic mean divisia index is used to analyze changes in emissions of air pollutants with a focus on the following five factors: coal pollution intensity (CPI), end-of-pipe treatment (EOP), the energy mix (EM), productive efficiency change (EFF), and production scale changes (PSC). Three pollutants are the main focus of this study: sulfur dioxide (SO2), dust, and soot. The novelty of this paper is focusing on the impact of the elimination policy on air pollution management in China by type of industry using the scale merit effect for pollution abatement technology change. First, the increase in SO2 emissions from Chinese industrial sectors because of the increase in the production scale is demonstrated. However, the EOP equipment that induced this change and improvements in energy efficiency has prevented an increase in SO2 emissions that is commensurate with the increase in production. Second, soot emissions were successfully reduced and controlled in all industries except the steel industry between 1998 and 2009, even though the production scale expanded for these industries. This reduction was achieved through improvements in EOP technology and in energy efficiency. Dust emissions decreased by nearly 65% between 1998 and 2009 in the Chinese industrial sectors. This successful reduction in emissions was achieved by implementing EOP technology and pollution prevention activities during the production processes, especially in the cement industry. Finally, pollution prevention in the cement industry is shown to result from production technology development rather than scale merit. © 2013 Elsevier Ltd. All rights reserved.
Estimating the burden of disease attributable to urban outdoor air pollution in South Africa in 2000
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Objectives To quantify the mortality burden attributed to urban outdoor air pollution in South Africa in 2000. Design The study followed comparative risk assessment (CRA) methodology developed by the World Heath Organization (WHO). In most urban areas, annual mean concentrations of particulate matter (PM) with diameters less than 10 μum (PM10) from monitoring network data and PM with diameters less than 2.5 μm (PM2.5) derived using a ratio method were weighted according to population size. PM10 and PM2.5 data from air-quality assessment studies in areas not covered by the network were also included. Population-attributable fractions calculated using risk coefficients presented in the WHO study were weighted by the proportion of the total population (33%) in urban environments, and applied to revised estimates of deaths and years of life lost (YLLs) for South Africa in 2000. Setting South Africa. Subjects Children under 5 years and adults 30 years and older. Outcome measures Mortality and YLLs from lung cancer and cardiopulmonary disease in adults (30 years and older), and from acute respiratory infections (ARIs) in children aged 0 - 4 years. Results Outdoor air pollution in urban areas in South Africa was estimated to cause 3.7% of the national mortality from cardiopulmonary disease and 5.1% of mortality attributable to cancers of the trachea, bronchus and lung in adults aged 30 years and older, and 1.1% of mortality from ARIs in children under 5 years of age. This amounts to 4 637 or 0.9% (95% uncertainty interval 0.3 - 1.5%) of all deaths and about 42 000 YLLs, or 0.4% (95% uncertainty interval 0.1 - 0.7%) of all YLLs in persons in South Africa in 2000. Conclusion Urban air pollution has under-recognised public health impacts in South Africa. Fossil fuel combustion emissions and traffic-related air pollution remain key targets for public health in South Africa.
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Background Little information exists regarding the interaction effects of obesity with long-term air pollution exposure on cardiovascular diseases (CVDs) and stroke in areas of high pollution. The aim of the present study is to examine whether obesity modifies CVD-related associations among people living in an industrial province of northeast China. Methods We studied 24,845 Chinese adults, aged 18 to 74 years old, from three Northeastern Chinese cities in 2009 utilizing a cross-sectional study design. Body weight and height were measured by trained observers. Overweight and obesity were defined as a body mass index (BMI) between 25–29.9 and ≥ 30 kg/m2, respectively. Prevalence rate and related risk factors of cardiovascular and cerebrovascular diseases were investigated by a questionnaire. Three-year (2006–2008) average concentrations of particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxides (NO2), and ozone (O3) were measured by fixed monitoring stations. All the participants lived within 1 km of air monitoring sites. Two-level logistic regression (personal level and district-specific pollutant level) was used to examine these effects, controlling for covariates. Results We observed significant interactions between exposure and obesity on CVDs and stroke. The associations between annual pollutant concentrations and CVDs and stroke were strongest in obese subjects (OR 1.15–1.47 for stroke, 1.33–1.59 for CVDs), less strong in overweight subjects (OR 1.22–1.35 for stroke, 1.07–1.13 for CVDs), and weakest in normal weight subjects (OR ranged from 0.98–1.01 for stroke, 0.93–1.15 for CVDs). When stratified by gender, these interactions were significant only in women. Conclusions Study findings indicate that being overweight and obese may enhance the effects of air pollution on the prevalence of CVDs and stroke in Northeastern metropolitan China. Further studies will be needed to investigate the temporality of BMI relative to exposure and onset of disease.
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Identifying inequalities in air pollution levels across population groups can help address environmental justice concerns. We were interested in assessing these inequalities across major urban areas in Australia. We used a land-use regression model to predict ambient nitrogen dioxide (NO2) levels and sought the best socio-economic and population predictor variables. We used a generalised least squares model that accounted for spatial correlation in NO2 levels to examine the associations between the variables. We found that the best model included the index of economic resources (IER) score as a non-linear variable and the percentage of non-Indigenous persons as a linear variable. NO2 levels decreased with increasing IER scores (higher scores indicate less disadvantage) in almost all major urban areas, and NO2 also decreased slightly as the percentage of non-Indigenous persons increased. However, the magnitude of differences in NO2 levels was small and may not translate into substantive differences in health.
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25 p.
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Se estudia la influencia de los siguientes factores sobre el valor del cociente de feofitinización DO 435 nm/DO 415 nm en el líquen Anaptychia ciliaris (L.) Kórber: edad del líquen, concentración final de pigmentos, trasplante de los líquenes a áreas distintas sobre sustratos diferentes o similares y el valor de pH del sustrato original o el adoptado tras el trasplante. Se discute la utilización de A. ciliaris como un bioindicador de la presencia de factorcs acidificantes en la atmósfera o en el agua de lluvia que provoquen la feofitinización de las clorofilas.
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Includes index.
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Thesis (Master's)--University of Washington, 2016-06
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Thesis (Master's)--University of Washington, 2016-06
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Air pollution levels were monitored continuously over a period of 4 weeks at four sampling sites along a busy urban corridor in Brisbane. The selected sites were representative of industrial and residential types of urban environment affected by vehicular traffic emissions. The concentration levels of submicrometer particle number, PM2.5, PM10, CO, and NOx were measured 5-10 meters from the road. Meteorological parameters and traffic flow rates were also monitored. The data were analysed in terms of the relationship between monitored pollutants and existing ambient air quality standards. The results indicate that the concentration levels of all pollutants exceeded the ambient air background levels, in certain cases by up to an order of magnitude. While the 24-hr average concentration levels did not exceed the standard, estimates for the annual averages were close to, or even higher than the annual standard levels.