178 resultados para PARTICULATE AIR-POLLUTION


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INTRODUCTION: The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure. METHODS: The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty. RESULTS: Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease. CONCLUSION: This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence-based policies and programs must be developed and implemented to address these risk factors at individual, household, and community levels.

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Mongolia has significant exposure to environmental risk factors because of poor environmental management and behaviors, and children are increasingly vulnerable to these threats. This study aimed to assess levels of exposure and summarize the evidence for associations between exposures to environmental risk factors and adverse health outcomes in Mongolia, with a particular focus on children. A systematic review was conducted using the PubMed, EMBASE, Web of Science, Global Health Library, CINAHL, CABI, Scopus, and mongolmed.mn electronic databases up to April 2014 . A total of 59 studies meeting the predetermined criteria were included. Results indicate that the Mongolian population has significant exposure to outdoor and indoor air pollution, metals, environmental tobacco smoke, and other chemical toxins, and these risk factors have been linked to respiratory and cardiovascular diseases among adults and respiratory diseases and neurodevelopmental disorders among children. Well-designed epidemiological investigations in vulnerable populations especially in pregnant women and children are recommended.

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Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

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Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

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Children are particularly susceptible to air pollution and schools are examples of urban microenvironments that can account for a large portion of children’s exposure to airborne particles. Thus this paper aimed to determine the sources of primary airborne particles that children are exposed to at school by analyzing selected organic molecular markers at 11 urban schools in Brisbane, Australia. Positive matrix factorization analysis identified four sources at the schools: vehicle emissions, biomass burning, meat cooking and plant wax emissions accounting for 45%, 29%, 16% and 7%, of the organic carbon respectively. Biomass burning peaked in winter due to prescribed burning of bushland around Brisbane. Overall, the results indicated that both local (traffic) and regional (biomass burning) sources of primary organic aerosols influence the levels of ambient particles that children are exposed at the schools. These results have implications for potential control strategies for mitigating exposure at schools.

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There is considerable scientific interest in personal exposure to ultrafine particles. Owing to their small size, these particles are able to penetrate deep into the lungs, where they may cause adverse respiratory, pulmonary and cardiovascular health effects. This article presents Bayesian hierarchical models for estimating and comparing inhaled particle surface area in the lung.

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The aim of this paper is to determine the suitability of solely stationary measurements for exposure assessment and management applications. For this purpose, quantified inhaled particle surface area (IPSA) doses using both stationary and personal particle exposure monitors were evaluated and compared.

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The Air Pollution Model and Chemical Transport Model (TAPM-CTM) framework has been tested and applied originally in Sydney to quantify particle and gaseous concentration (Cope et al, 2014). However, the model performance had not been tested in the south-eastern Queensland region (SEQR), Australia.

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The Australian food system significantly contributes to a range of key environmental issues including harmful greenhouse gas emissions, air pollution, soil desertification, biodiversity loss and water scarcity. At the same time, the Australian s food system is a key cause of public health nutrition issues that stem from the co-existence of over- and under-consumption of dietary energy and nutrients. Within these challenges lie synergies and opportunities because a diet that has a lower environmental impact generally aligns with good nutrition. Australian State and Federal initiatives to influence food consumption patterns focus on individual body weight and ‘soft law’ interventions. These regulatory approaches, by focusing on select symptoms of food system failures, are fragmented, reductionist and inefficient. In order to illustrate this point, this paper will explore Australian regulatory responses to diet-related illnesses. The analysis will support the argument that only when regulatory responses to diets become embedded within reform of the current food system will substantial improvements to human and planetary health be achieved.

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Exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with adverse health outcomes. Concentrations of urinary PAH metabolites (OH-PAHs) provide an integrated measure of human exposure to PAHs but measurement of urinary OH-PAHs has not been done in Australia and rarely in Vietnam, where air pollution is of concern. In this study, we assessed exposure to PAHs in 16 participants living in Brisbane, Australia and Hanoi, Vietnam, with 4 participants travelling between the two cities during the monitoring period. A total of 312 first morning urine samples were collected over 10 weeks and were analysed for nine OH-PAHs. Concentrations of the urinary OH-PAHs were 2–10 times higher in participants from Hanoi than those from Brisbane. For example, the median concentrations of 1-hydroxypyrene were 292 pg/mL in Hanoi, compared to 64 pg/mL in Brisbane. For participants travelling from Brisbane to Hanoi and back, differences in exposure to PAHs in these two cities resulted in corresponding changes of urinary OH-PAH concentrations, demonstrating that the more polluted environment in Hanoi was likely the source for higher PAH exposure there.

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The objective of this study is to examine the association between ambient temperature and children’s lung function in Baotou, China. We recruited 315 children (8–12 years) from Baotou, China in the spring of 2004, 2005, and 2006. They performed three successive forced expiratory measurements three times daily (morning, noon, and evening) for about 5 weeks. The highest peak expiratory flow (PEF) was recorded for each session. Daily data on ambient temperature, relative humidity, and air pollution were monitored during the same period. Mixed models with a distributed lag structure were used to examine the effects of temperature on lung function while adjusting for individual characteristics and environmental factors. Low temperatures were significantly associated with decreases in PEF. The effects lasted for lag 0–2 days. For all participants, the cumulative effect estimates (lag 0–2 days) were −1.44 (−1.93, −0.94) L/min, −1.39 (−1.92, −0.86) L/min, −1.40 (−1.97, −0.82) L/min, and −1.28 (−1.69, −0.88) L/min for morning, noon, evening, and daily mean PEF, respectively, associated with 1 °C decrease in daily mean temperature. Generally, the effects of temperature were slightly stronger in boys than in girls for noon, evening, and daily mean PEF, while the effects were stronger in girls for morning PEF. PM2.5 had joint effects with temperature on children’s PEF. Higher PM2.5 increased the impacts of low temperature. Low ambient temperatures are associated with lower lung function in children in Baotou, China. Preventive health policies will be required for protecting children from the cold weather.