177 resultados para Air pollution


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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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Ultrafine particles are particles that are less than 0.1 micrometres (µm) in diameter. Due to their very small size they can penetrate deep into the lungs, and potentially cause more damage than larger particles. The Ultrafine Particles from Traffic Emissions and Children’s Health (UPTECH) study is the first Australian epidemiological study to assess the health effects of ultrafine particles on children’s health in general and peripheral airways in particular. The study is being conducted in Brisbane, Australia. Continuous indoor and outdoor air pollution monitoring was conducted within each of the twenty five participating school campuses to measure particulate matter, including in the ultrafine size range, and gases. Respiratory health effects were evaluated by conducting the following tests on participating children at each school: spirometry, forced oscillation technique (FOT) and multiple breath nitrogen washout test (MBNW) (to assess airway function), fraction of exhaled nitric oxide (FeNO, to assess airway inflammation), blood cotinine levels (to assess exposure to second-hand tobacco smoke), and serum C-reactive protein (CRP) levels (to measure systemic inflammation). A pilot study was conducted prior to commencing the main study to assess the feasibility and reliably of measurement of some of the clinical tests that have been proposed for the main study. Air pollutant exposure measurements were not included in the pilot study.

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BACKGROUND Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time. METHODS We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. FINDINGS In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2-7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5-7·0]), and alcohol use (5·5% [5·0-5·9]). In 1990, the leading risks were childhood underweight (7·9% [6·8-9·4]), household air pollution from solid fuels (HAP; 7·0% [5·6-8·3]), and tobacco smoking including second-hand smoke (6·1% [5·4-6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2-10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water and sanitation accounting for 0·9% (0·4-1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, most of Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania. INTERPRETATION Worldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children.

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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.

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Background Heatwaves have a significant impact on population health including both morbidity and mortality. In this study we examined the association between heatwaves and emergency hospital admissions (EHAs) for renal diseases in children (aged 0–14 years) in Brisbane, Australia. Methods Daily data on EHAs for renal diseases in children and exposure to temperature and air pollution were obtained for Brisbane city from January 1, 1996 to December 31, 2005. A time-stratified case-crossover design was used to compare the risks for renal diseases between heatwave and non-heatwave periods. Results There were 1565 EHAs for renal diseases in children during the study period. Heatwaves exhibited a significant impact on EHAs for renal diseases in children after adjusting for confounding factors (odds ratio: 3.6; 95% confidence interval: 1.4–9.5). The risk estimates differed with lags and the use of different heatwave definitions. Conclusions There was a significant increase in EHAs for renal diseases in children during heatwaves in Brisbane, a subtropical city where people are well accustomed to warm weather. This finding may have significant implications for pediatric renal care, particularly in subtropical and tropical regions.

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To study the relation between temperature and mortality by estimating the temperature-related mortality in Beijing, Shanghai, and Guangzhou. METHODS: Data of daily mortality, weather and air pollution in the three cities were collected. A distributed lag nonlinear model was established and used in analyzing the effects of temperature on mortality. Current and future net temperature-related mortality was estimated. RESULTS: The association between temperature and mortality was J-shaped, with an increased death risk of both hot and cold temperature in these cities. The effects of cold temperature on health lasted longer than those of hot temperature. The projected temperature-related mortality increased with the decreased cold-related mortality. The mortality was higher in Guangzhou than in Beijing and Shanghai. CONCLUSION: The impact of temperature on health varies in the 3 cities of China, which may have implications for climate policy making in China.

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Background Little evidence is available about the association between temperature and cerebrovascular mortality in China. This study aims to examine the effects of ambient temperature on cerebrovascular mortality in different climatic zones in China. Method We obtained daily data on weather conditions, air pollution and cerebrovascular deaths from five cities (Beijing, Tianjin, Shanghai, Wuhan, and Guangzhou) in China during 2004-2008. We examined city-specific associations between ambient temperature and the cerebrovascular mortality, while adjusting for season, long-term trends, day of the week, relative humidity and air pollution. We examined cold effects using a 1°C decrease in temperature below a city-specific threshold, and hot effects using a 1°C increase in temperature above a city-specific threshold. We used a meta-analysis to summarize the cold and hot effects across the five cities. Results Beijing and Tianjin (with low mean temperature) had lower thresholds than Shanghai, Wuhan and Guangzhou (with high mean temperature). In Beijing, Tianjin, Wuhan and Guangzhou cold effects were delayed, while in Shanghai there was no or short induction. Hot effects were acute in all five cities. The cold effects lasted longer than hot effects. The hot effects were followed by mortality displacement. The pooled relative risk associated with a 1°C decrease in temperature below thresholds (cold effect) was 1.037 (95% confidence interval (CI): 1.020, 1.053). The pooled relative risk associated with a 1°C increase in temperature above thresholds (hot effect) was 1.014 (95% CI: 0.979, 1.050). Conclusion Cold temperatures are significantly associated with cerebrovascular mortality in China, while hot effect is not significant. People in colder climate cities were sensitive to hot temperatures, while people in warmer climate cities were vulnerable to cold temperature.