205 resultados para Air quality monitoring stations
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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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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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The current state of knowledge in relation to first flush does not provide a clear understanding of the role of rainfall and catchment characteristics in influencing this phenomenon. This is attributed to the inconsistent findings from research studies due to the unsatisfactory selection of first flush indicators and how first flush is defined. The research study discussed in this thesis provides the outcomes of a comprehensive analysis on the influence of rainfall and catchment characteristics on first flush behaviour in residential catchments. Two sets of first flush indicators are introduced in this study. These indicators were selected such that they are representative in explaining in a systematic manner the characteristics associated with first flush. Stormwater samples and rainfall-runoff data were collected and recorded from stormwater monitoring stations established at three urban catchments at Coomera Waters, Gold Coast, Australia. In addition, historical data were also used to support the data analysis. Three water quality parameters were analysed, namely, total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The data analyses were primarily undertaken using multi criteria decision making methods, PROMETHEE and GAIA. Based on the data obtained, the pollutant load distribution curve (LV) was determined for the individual rainfall events and pollutant types. Accordingly, two sets of first flush indicators were derived from the curve, namely, cumulative load wash-off for every 10% of runoff volume interval (interval first flush indicators or LV) from the beginning of the event and the actual pollutant load wash-off during a 10% increment in runoff volume (section first flush indicators or P). First flush behaviour showed significant variation with pollutant types. TSS and TP showed consistent first flush behaviour. However, the dissolved fraction of TN showed significant differences to TSS and TP first flush while particulate TN showed similarities. Wash-off of TSS, TP and particulate TN during the first 10% of the runoff volume showed no influence from corresponding rainfall intensity. This was attributed to the wash-off of weakly adhered solids on the catchment surface referred to as "short term pollutants" or "weakly adhered solids" load. However, wash-off after 10% of the runoff volume showed dependency on the rainfall intensity. This is attributed to the wash-off of strongly adhered solids being exposed when the weakly adhered solids diminish. The wash-off process was also found to depend on rainfall depth at the end part of the event as the strongly adhered solids are loosened due to impact of rainfall in the earlier part of the event. Events with high intensity rainfall bursts after 70% of the runoff volume did not demonstrate first flush behaviour. This suggests that rainfall pattern plays a critical role in the occurrence of first flush. Rainfall intensity (with respect to the rest of the event) that produces 10% to 20% runoff volume play an important role in defining the magnitude of the first flush. Events can demonstrate high magnitude first flush when the rainfall intensity occurring between 10% and 20% of the runoff volume is comparatively high while low rainfall intensities during this period produces low magnitude first flush. For events with first flush, the phenomenon is clearly visible up to 40% of the runoff volume. This contradicts the common definition that first flush only exists, if for example, 80% of the pollutant mass is transported in the first 30% of runoff volume. First flush behaviour for TN is different compared to TSS and TP. Apart from rainfall characteristics, the composition and the availability of TN on the catchment also play an important role in first flush. The analysis confirmed that events with low rainfall intensity can produce high magnitude first flush for the dissolved fraction of TN, while high rainfall intensity produce low dissolved TN first flush. This is attributed to the source limiting behaviour of dissolved TN wash-off where there is high wash-off during the initial part of a rainfall event irrespective of the intensity. However, for particulate TN, the influence of rainfall intensity on first flush characteristics is similar to TSS and TP. The data analysis also confirmed that first flush can occur as high magnitude first flush, low magnitude first flush or non existence of first flush. Investigation of the influence of catchment characteristics on first flush found that the key factors that influence the phenomenon are the location of the pollutant source, spatial distribution of the pervious and impervious surfaces in the catchment, drainage network layout and slope of the catchment. This confirms that first flush phenomenon cannot be evaluated based on a single or a limited set of parameters as a number of catchment characteristics should be taken into account. Catchments where the pollutant source is located close to the outlet, a high fraction of road surfaces, short travel time to the outlet, with steep slopes can produce high wash-off load during the first 50% of the runoff volume. Rainfall characteristics have a comparatively dominant impact on the wash-off process compared to the catchment characteristics. In addition, the pollutant characteristics also should be taken into account in designing stormwater treatment systems due to different wash-off behaviour. Analysis outcomes confirmed that there is a high TSS load during the first 20% of the runoff volume followed by TN which can extend up to 30% of the runoff volume. In contrast, high TP load can exist during the initial and at the end part of a rainfall event. This is related to the composition of TP available for the wash-off.
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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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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.
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Ultrafine particles (UFP; diameter less than 100 nm) are ubiquitous in urban air, and an acknowledged risk to human health. Globally, the major source for urban outdoor UFP concentrations is motor traffic. Ongoing trends towards urbanisation and expansion of road traffic are anticipated to further increase population exposure to UFPs. Numerous experimental studies have characterised UFPs in individual cities, but an integrated evaluation of emissions and population exposure is still lacking. Our analysis suggest that average exposure to outdoor UFPs in Asian cities is about four-times larger than those in European cities but impacts on human health are largely unknown. This article reviews some fundamental drivers of UFP emissions and dispersion, and highlights unresolved challenges, as well as recommendations to ensure sustainable urban development whilst minimising any possible adverse health impacts.
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In January 2011, Brisbane, Australia, experienced a major river flooding event. We aimed to investigate its effects on air quality and assess the role of prompt cleaning activities in reducing the airborne exposure risk. A comprehensive, multi-parameter indoor and outdoor measurement campaign was conducted in 41 residential houses, 2 and 6 months after the flood. The median indoor air concentrations of supermicrometer particle number (PN), PM10, fungi and bacteria 2 months after the flood were comparable to those previously measured in Brisbane. These were 2.88 p cm-3, 15 µg m-3, 804 cfu m-3 and 177 cfu m-3 for flood-affected houses (AFH), and 2.74 p cm-3, 15 µg m-3, 547 cfu m-3 and 167 cfu m-3 for non-affected houses (NFH), respectively. The I/O (indoor/outdoor) ratios of these pollutants were 1.08, 1.38, 0.74 and 1.76 for AFH and 1.03, 1.32, 0.83 and 2.17 for NFH, respectively. The average of total elements (together with transition metals) in indoor dust was 2296 ± 1328 µg m-2 for AFH and 1454 ± 678 µg m-2 for NFH, respectively. In general, the differences between AFH and NFH were not statistically significant, implying the absence of a measureable effect on air quality from the flood. We postulate that this was due to the very swift and effective cleaning of the flooded houses by 60,000 volunteers. Among the various cleaning methods, the use of both detergent and bleach was the most efficient at controlling indoor bacteria. All cleaning methods were equally effective for indoor fungi. This study provides quantitative evidence of the significant impact of immediate post-flood cleaning on mitigating the effects of flooding on indoor bioaerosol contamination and other pollutants.
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The charge and chemical composition of ambient particles in an urban environment were determined using a Neutral Particle and Air Ion Spectrometer and an Aerodyne compact Time-Of-Flight Aerosol Mass Spectrometer. Particle formation and growth events were observed on 20 of the 36 days of sampling, with eight of these events classified as strong. During these events, peaks in the concentration of intermediate and large ions were followed by peaks in the concentration of ammonium and sulphate, which were not observed in the organic fraction. Comparison of days with and without particle formation events revealed that ammonium and sulphate were the dominant species on particle formation days while high concentrations of biomass burning OA inhibited particle growth. Analyses of the degree of particle neutralisation lead us to conclude that an excess of ammonium enabled particle formation and growth. In addition, the large ion concentration increased sharply during particle growth, suggesting that during nucleation the neutral gaseous species ammonia and sulphuric acid react to form ammonium and sulphate ions. Overall, we conclude that the mechanism of particle formation and growth involved ammonia and sulphuric acid, with limited input from organics.
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This study demonstrates a novel method for testing the hypothesis that variations in primary and secondary particle number concentration (PNC) in urban air are related to residual fuel oil combustion at a coastal port lying 30 km upwind, by examining the correlation between PNC and airborne particle composition signatures chosen for their sensitivity to the elemental contaminants present in residual fuel oil. Residual fuel oil combustion indicators were chosen by comparing the sensitivity of a range of concentration ratios to airborne emissions originating from the port. The most responsive were combinations of vanadium and sulfur concentration ([S], [V]) expressed as ratios with respect to black carbon concentration ([BC]). These correlated significantly with ship activity at the port and with the fraction of time during which the wind blew from the port. The average [V] when the wind was predominantly from the port was 0.52 ng.m-3 (87%) higher than the average for all wind directions and 0.83 ng.m-3 (280%) higher than that for the lowest vanadium yielding wind direction considered to approximate the natural background. Shipping was found to be the main source of V impacting urban air quality in Brisbane. However, contrary to the stated hypothesis, increases in PNC related measures did not correlate with ship emission indicators or ship traffic. Hence at this site ship emissions were not found to be a major contributor to PNC compared to other fossil fuel combustion sources such as road traffic, airport and refinery emissions.
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Particle number concentrations vary significantly with environment and, in this study, we attempt to assess the significance of these differences. Towards this aim, we reviewed 85 papers that have reported particle number concentrations levels at 126 sites covering different environments. We grouped the results into eight categories according to measurement location including: road tunnel, on-road, road-side, street canyon, urban, urban background, rural, and clean background. Median values were calculated for each category. This review was restricted to papers that presented concentrations numerically. The majority of the reports were based on either CPC or SMPS measurements, with a limited number of papers reporting results from both instruments at the same site. Hence there were several overlaps between the number of CPC and SMPS measuring sites. Most of the studies reported multiple measurements at a given study site, while some studies included results from more than one site. From these reports, the overall median value for each location category was calculated...
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Occupational standards concerning the allowable concentrations of chemical compounds in the ambient air of workplaces have been established in several countries at national levels. With the integration of the European Union, a need exists for establishing harmonized Occupational Exposure Limits. For analytical developments, it is apparent that methods for speciation or fractionation of carcinogenic metal compounds will be of increasing practical importance for standard setting. Criteria of applicability under field conditions, cost-effectiveness, and robustness are practical driving forces for new developments. When the European Union issued a list of 62 chemical substances with Occupational Exposure Limits in 2000, 25 substances received a 'skin' notation. The latter indicates that toxicologically significant amounts may be taken up via the skin. Similar notations exist on national levels. For such substances, monitoring concentrations in ambient air will not be sufficient; biological monitoring strategies will gain further importance in the medical surveillance of workers who are exposed to such compounds. Proceedings in establishing legal frameworks for a biological monitoring of chemical exposures within Europe are paralleled by scientific advances in this field. A new aspect is the possibility of a differential adduct monitoring, using blood proteins of different half-life or lifespan. This technique allows differentiation between long-term mean exposure to reactive chemicals and short-term episodes, for example, by accidental overexposure. For further analytical developments, the following issues have been addressed as being particularly important: New dose monitoring strategies, sensitive and reliable methods for detection of DNA adducts, cytogenetic parameters in biological monitoring, methods to monitor exposure to sensitizing chemicals, and parameters for individual susceptibilities to chemical toxicants.
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Outdoor air pollution is a killer. A recent report from the World Health Organization estimated that 3.7 million deaths per year are due to outdoor air pollution. Most of these deaths are in low and middle income countries, with China being the country that often springs to mind. However, Australia still has a relatively big air pollution problem with an estimated 3,000 deaths per year. Traffic pollution is the major contributor to urban air pollution in Australia. Extreme events, such dust storms, bushfires and the recent coal fire in Morwell, dramatically increase pollution levels (for days or weeks) and are also very hazardous to health. Australian governments in the last 30 years have committed to improving air quality, and policies have been discussed and implemented with the aim of creating cleaner air. One key policy measure is the National Environment Protection Measures for air quality. These set standards for six important outdoor pollutants. Their key goal is to create “ambient air quality that allows for the adequate protection of human health and wellbeing”.
Resumo:
Air pollution is a persistent problem in urban areas, and traffic emissions are a major cause of poor air quality. Policies to curb pollution levels often involve raising the price of using private vehicles, for example, congestion charges. We were interested in whether higher fuel prices were associated with decreased air pollution levels. We examined an association between diesel and petrol prices and four traffic-related pollutants in Brisbane from 2010 to 2013. We used a regression model and examined pollution levels up to 16 days after the price change. Higher diesel prices were associated with statistically significant short-term reductions in carbon monoxide and nitrogen oxides. Changes in petrol prices had no impact on air pollution. Raising diesel taxes in Australia could be justified as a public health measure. As raising taxes is politically unpopular, an alternative political approach would be to remove schemes that put a downward pressure on fuel prices, such as industry subsidies and shopping vouchers that give fuel discounts.