940 resultados para 770701 Air quality


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Heat islands are a significant problem in urban spaces worldwide. The phenomenon occurs when air and surface temperatures in urban areas significantly exceed those experienced in nearby rural areas. There are two main causes of heat islands. The first is the use of highly absorptive construction materials in buildings and infrastructure, which soak up heat and radiate it back into the immediate surroundings. These materials, including but not limited to concrete, steel, asphalt and stone, are usually impermeable and so do not embody moisture that could dissipate some of the absorbed heat. The second cause relates to urban form, where the canyon-like configurations of buildings and streets channel and trap heat from the sun. In both cases, an absence of greenery and other soft landscaping can compound the problem by lowering capacity for cooling through shading and evotranspiration. Incidences of heat islands increase as urban areas swell in size and cover more land area, making the phenomenon an unwelcome side effect of global trends towards increased urbanisation. Heat islands create serious problems, including increased energy demand for cooling, declining air quality and heat stress for people and animals. In very severe cases, heat islands can compound the effects of high urban temperatures, leading to increased human mortality...

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Generally, the magnitude of pollutant emissions from diesel engines is ultimately coupled to the structure of fuel molecules. The presence of oxygen, level of unsaturation and the carbon chain length of respective molecules influence the combustion chemistry. It is speculated that increased oxygen content in the fuel may lead to the increased oxidative potential (Stevanovic, S. 2013). Also, upon the exposure to UV and ozone in the atmosphere, the chemical composition of the exhaust is changed. The presence of an oxidant and UV is triggering the cascade of photochemical reactions as well as the partitioning of semi-volatile compounds between the gas and particle phase. To gain an insight into the relationship between the molecular structures of the esters, their volatile organic content and the potential toxicity of diesel exhaust particulate matter, measurements were conducted on a modern common rail diesel engine. This research also investigates the contribution of atmospheric conditions on the transfer of semi-volatile fraction of diesel exhaust from the gas phase to the particle phase and the extent to which semi-volatile compounds (SVOCs) are related to the oxidative potential, expressed through the concentration of reactive oxygen species (ROS) (Stevanovic, S. 2013)...

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Generating nano-sized materials of a controlled size and chemical composition is essential for the manufacturing of materials with enhanced properties on an industrial scale, as well as for research purposes, such as toxicological studies. Among the generation methods for airborne nanoparticles (also known as aerosolisation methods), liquid-phase techniques have been widely applied due to the simplicity of their use and their high particle production rate. The use of a collison nebulizer is one such technique, in which the atomisation takes place as a result of the liquid being sucked into the air stream and injected toward the inner walls of the nebulizer reservoir via nozzles, before the solution is dispersed. Despite the above-mentioned benefits, this method also falls victim to various sources of impurities (Knight and Petrucci 2003; W. LaFranchi, Knight et al. 2003). Since these impurities can affect the characterization of the generated nanoparticles, it is crucial to understand and minimize their effect.

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A Neutral cluster and Air Ion Spectrometer (NAIS) was used to monitor the concentration of airborne ions on 258 full days between Nov 2011 and Dec 2012 in Brisbane, Australia. The air was sampled from outside a window on the sixth floor of a building close to the city centre, approximately 100 m away from a busy freeway. The NAIS detects all ions and charged particles smaller than 42 nm. It was operated in a 4 min measurement cycle, with ion data recorded at 10 s intervals over 2 min during each cycle. The data were analysed to derive the diurnal variation of small, large and total ion concentrations in the environment. We adapt the definition of Horrak et al (2000) and classify small ions as molecular clusters smaller than 1.6 nm and large ions as charged particles larger than this size...

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The aim of this study was to quantify school children’s exposure to ultrafine particles (UFP) in urban environments. The study was conducted as part of a larger epidemiological project aiming to determine the association between exposures to UFPs and children’s health, titled “Ultrafine Particles from Traffic Emissions and Children’s Health”1 (UPTECH). School children aged 8-11 years old at 24 state schools within the Brisbane Metropolitan Area participated in the present study. This paper presents the methodology and results for calculating deposited UFP surface area in the alveolar region (dose), where UFP deposition is more efficient for particles larger than 6 nm...

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The issue of particle emissions from diesel engines is still a matter of concern due its deleterious effects both on human health and environment(Ristovski et al., 2012). Recently, International Agency for Research on Cancer (IARC) inclusion of diesel engine exhaust particles as carcinogenic to human health added a new margin on it. Apart from the use of after treatment technology, biodiesel is also considered as potential way to reduce particle emission alongside with other emissions(Xue, Grift, & Hansen, 2011). Global biodiesel production is still reasonably small compared to its counterpart fossil diesel, but even this small amount comes from a wide variety of feed stocks. Contrary to fossil diesel, the important physicochemical properties of biodiesel vary among different feed stocks(Hoekman, Broch, Robbins, Ceniceros, & Natarajan, 2012).

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Airborne particles have been shown to be associated with a wide range of adverse health effects, which has led to a recent increase in medical research to gain better insight into their health effects. However, accurate evaluation of the exposure-dose-response relationship is highly dependent on the ability to track actual exposure levels of people to airborne particles. This is quite a complex task, particularly in relation to submicrometer and ultrafine particles, which can vary quite significantly in terms of particle surface area and number concentrations. Therefore, suitable monitors that can be worn for measuring personal exposure to these particles are needed. This paper presents an evaluation of the metrological performance of six diffusion charger sensors, NanoTracer (Philips Aerasense) monitors, when measuring particle number and surface area concentrations, as well as particle number distribution mean when compared to reference instruments. Tests in the laboratory (by generating monodisperse and polydisperse aerosols) and in the field (using natural ambient particles) were designed to evaluate the response of these devices under both steady-state and dynamics conditions. Results showed that the NanoTracers performed well when measuring steady state aerosols, however they strongly underestimated actual concentrations during dynamic response testing. The field experiments also showed that, when the majority of the particles were smaller than 20 nm, which occurs during particle formation events in the atmosphere, the NanoTracer underestimated number concentration quite significantly. Even though the NanoTracer can be used for personal monitoring of exposure to ultrafine particles, it also has limitations which need to be considered in order to provide meaningful results.

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A technique for analysing exhaust emission plumes from unmodified locomotives under real world conditions is described and applied to the task of characterizing plumes from railway trains servicing an Australian shipping port. The method utilizes the simultaneous measurement, downwind of the railway line, of the following pollutants; particle number, PM2.5 mass fraction, SO2, NOx and CO2, with the last of these being used as an indicator of fuel combustion. Emission factors are then derived, in terms of number of particles and mass of pollutant emitted per unit mass of fuel consumed. Particle number size distributions are also presented. The practical advantages of the method are discussed including the capacity to routinely collect emission factor data for passing trains and to thereby build up a comprehensive real world database for a wide range of pollutants. Samples from 56 train movements were collected, analyzed and presented. The quantitative results for emission factors are: EF(N)=(1.7±1)×1016 kg-1, EF(PM2.5)= (1.1±0.5) g·kg-1, EF(NOx)= (28±14) g·kg-1, and EF(SO2 )= (1.4±0.4) g·kg-1. The findings are compared with comparable previously published work. Statistically significant (p<α, α=0.05) correlations within the group of locomotives sampled were found between the emission factors for particle number and both SO2 and NOx.

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This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates. The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.

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Scores of well-researched individual papers and posters specifically or indirectly addressing the occurrence, measurement or exposure impacts of chemicals in buildings were presented at 2012 Healthy Buildings Conference. Many of these presentations offered advances in sampling and characterisation of chemical pollutants while others extended the frontiers of knowledge on the emission, adsorption, risk, fate and compositional levels of chemicals in indoor and outdoor microenvironments. Several modelled or monitored indoor chemistry, including processes that generated secondary pollutants. This article provides an overview of the state of knowledge on healthy buildings based on papers presented in chemistry sessions at Healthy Buildings 2012 (HB2012) Conference. It also suggests future directions in healthy buildings research.

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Despite the existence of air quality guidelines in Australia and New Zealand, the concentrations of particulate matter have exceeded these guidelines on several occasions. To identify the sources of particulate matter, examine the contributions of the sources to the air quality at specific areas and estimate the most likely locations of the sources, a growing number of source apportionment studies have been conducted. This paper provides an overview of the locations of the studies, salient features of the results obtained and offers some perspectives for the improvement of future receptor modelling of air quality in these countries. The review revealed that because of its advantages over alternative models, Positive Matrix Factorisation (PMF) was the most commonly applied model in the studies. Although there were differences in the sources identified in the studies, some general trends were observed. While biomass burning was a common problem in both countries, the characteristics of this source varied from one location to another. In New Zealand, domestic heating was the highest contributor to particle levels on days when the guidelines were exceeded. On the other hand, forest back-burning was a concern in Brisbane while marine aerosol was a major source in most studies. Secondary sulphate, traffic emissions, industrial emissions and re-suspended soil were also identified as important sources. Some unique species, for example, volatile organic compounds and particle size distribution were incorporated into some of the studies with results that have significant ramifications for the improvement of air quality. Overall, the application of source apportionment models provided useful information that can assist the design of epidemiological studies and refine air pollution reduction strategies in Australia and New Zealand.

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Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

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This thesis is the first comprehensive study of important parameters relating to aerosols' impact on climate and human health, namely spatial variation, particle size distribution and new particle formation. We determined the importance of spatial variation of particle number concentration in microscale environments, developed a method for particle size parameterisation and provided knowledge about the chemistry of new particle formation. This is a significant contribution to our understanding of processes behind the transformation and dynamics of urban aerosols. This PhD project included extensive measurements of air quality parameters using state of the art instrumentation at each of the 25 sites within the Brisbane metropolitan area and advanced statistical analysis.

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Efforts to reduce carbon emissions in the buildings sector have been focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants,i something with much greater economic returns than energy savings. Reducing energy demand in green commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This paper outlines an investigation into these factors and focuses on better understanding the performance of and interaction between: design elements, internal environmental quality, occupant experience, tenant/leasing agreements, and building regulation and management. In doing so the paper presents a framework for improving energy efficiency in existing commercial buildings by considering a range of interconnected and synergistic elements.

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Although both the size and chemical composition of ambient particles are important parameters in determining their toxicities, their relative contributions are unclear (Heal et al., 2012). Children are particularly at risk to the detrimental health effects that have been linked to long term exposure to airborne particles (See e.g. Ruckerl et al., 2011). However, there is currently limited understanding of the health effects in children due to long term exposure to airborne particles. Schools are locations within an urban environment where children experience significant exposure to vehicle emissions, and to date there is limited information assessing children’s exposure at school. This study is a part of a large project aimed at gaining a holistic picture of the exposure of children to traffic related pollutants. In the current paper, results from the investigation of the elemental composition of airborne particle at urban schools are presented.