987 resultados para PM2.5


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Motor vehicles are major emitters of gaseous and particulate pollution in urban areas, and exposure to particulate pollution can have serious health effects, ranging from respiratory and cardiovascular disease to mortality. Motor vehicle tailpipe particle emissions span a broad size range from 0.003-10µm, and are measured as different subsets of particle mass concentrations or particle number count. However, no comprehensive inventories currently exist in the international published literature covering this wide size range. This paper presents the first published comprehensive inventory of motor vehicle tailpipe particle emissions covering the full size range of particles emitted. The inventory was developed for urban South-East Queensland by combining two techniques from distinctly different disciplines, from aerosol science and transport modelling. A comprehensive set of particle emission factors were combined with traffic modelling, and tailpipe particle emissions were quantified for particle number (ultrafine particles), PM1, PM2.5 and PM10 for light and heavy duty vehicles and buses. A second aim of the paper involved using the data derived in this inventory for scenario analyses, to model the particle emission implications of different proportions of passengers travelling in light duty vehicles and buses in the study region, and to derive an estimate of fleet particle emissions in 2026. It was found that heavy duty vehicles (HDVs) in the study region were major emitters of particulate matter pollution, and although they contributed only around 6% of total regional vehicle kilometres travelled, they contributed more than 50% of the region’s particle number (ultrafine particles) and PM1 emissions. With the freight task in the region predicted to double over the next 20 years, this suggests that HDVs need to be a major focus of mitigation efforts. HDVs dominated particle number (ultrafine particles) and PM1 emissions; and LDV PM2.5 and PM10 emissions. Buses contributed approximately 1-2% of regional particle emissions.

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Emissions from airport operations are of significant concern because of their potential impact on local air quality and human health. The currently limited scientific knowledge of aircraft emissions is an important issue worldwide, when considering air pollution associated with airport operation, and this is especially so for ultrafine particles. This limited knowledge is due to scientific complexities associated with measuring aircraft emissions during normal operations on the ground. In particular this type of research has required the development of novel sampling techniques which must take into account aircraft plume dispersion and dilution as well as the various particle dynamics that can affect the measurements of the aircraft engine plume from an operational aircraft. In order to address this scientific problem, a novel mobile emission measurement method called the Plume Capture and Analysis System (PCAS), was developed and tested. The PCAS permits the capture and analysis of aircraft exhaust during ground level operations including landing, taxiing, takeoff and idle. The PCAS uses a sampling bag to temporarily store a sample, providing sufficient time to utilize sensitive but slow instrumental techniques to be employed to measure gas and particle emissions simultaneously and to record detailed particle size distributions. The challenges in relation to the development of the technique include complexities associated with the assessment of the various particle loss and deposition mechanisms which are active during storage in the PCAS. Laboratory based assessment of the method showed that the bag sampling technique can be used to accurately measure particle emissions (e.g. particle number, mass and size distribution) from a moving aircraft or vehicle. Further assessment of the sensitivity of PCAS results to distance from the source and plume concentration was conducted in the airfield with taxiing aircraft. The results showed that the PCAS is a robust method capable of capturing the plume in only 10 seconds. The PCAS is able to account for aircraft plume dispersion and dilution at distances of 60 to 180 meters downwind of moving a aircraft along with particle deposition loss mechanisms during the measurements. Characterization of the plume in terms of particle number, mass (PM2.5), gaseous emissions and particle size distribution takes only 5 minutes allowing large numbers of tests to be completed in a short time. The results were broadly consistent and compared well with the available data. Comprehensive measurements and analyses of the aircraft plumes during various modes of the landing and takeoff (LTO) cycle (e.g. idle, taxi, landing and takeoff) were conducted at Brisbane Airport (BNE). Gaseous (NOx, CO2) emission factors, particle number and mass (PM2.5) emission factors and size distributions were determined for a range of Boeing and Airbus aircraft, as a function of aircraft type and engine thrust level. The scientific complexities including the analysis of the often multimodal particle size distributions to describe the contributions of different particle source processes during the various stages of aircraft operation were addressed through comprehensive data analysis and interpretation. The measurement results were used to develop an inventory of aircraft emissions at BNE, including all modes of the aircraft LTO cycle and ground running procedures (GRP). Measurements of the actual duration of aircraft activity in each mode of operation (time-in-mode) and compiling a comprehensive matrix of gas and particle emission rates as a function of aircraft type and engine thrust level for real world situations was crucial for developing the inventory. The significance of the resulting matrix of emission rates in this study lies in the estimate it provides of the annual particle emissions due to aircraft operations, especially in terms of particle number. In summary, this PhD thesis presents for the first time a comprehensive study of the particle and NOx emission factors and rates along with the particle size distributions from aircraft operations and provides a basis for estimating such emissions at other airports. This is a significant addition to the scientific knowledge in terms of particle emissions from aircraft operations, since the standard particle number emissions rates are not currently available for aircraft activities.

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The effects of particulate matter on environment and public health have been widely studied in recent years. A number of studies in the medical field have tried to identify the specific effect on human health of particulate exposure, but agreement amongst these studies on the relative importance of the particles’ size and its origin with respect to health effects is still lacking. Nevertheless, air quality standards are moving, as the epidemiological attention, towards greater focus on the smaller particles. Current air quality standards only regulate the mass of particulate matter less than 10 μm in aerodynamic diameter (PM10) and less than 2.5 μm (PM2.5). The most reliable method used in measuring Total Suspended Particles (TSP), PM10, PM2.5 and PM1 is the gravimetric method since it directly measures PM concentration, guaranteeing an effective traceability to international standards. This technique however, neglects the possibility to correlate short term intra-day variations of atmospheric parameters that can influence ambient particle concentration and size distribution (emission strengths of particle sources, temperature, relative humidity, wind direction and speed and mixing height) as well as human activity patterns that may also vary over time periods considerably shorter than 24 hours. A continuous method to measure the number size distribution and total number concentration in the range 0.014 – 20 μm is the tandem system constituted by a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS). In this paper, an uncertainty budget model of the measurement of airborne particle number, surface area and mass size distributions is proposed and applied for several typical aerosol size distributions. The estimation of such an uncertainty budget presents several difficulties due to i) the complexity of the measurement chain, ii) the fact that SMPS and APS can properly guarantee the traceability to the International System of Measurements only in terms of number concentration. In fact, the surface area and mass concentration must be estimated on the basis of separately determined average density and particle morphology. Keywords: SMPS-APS tandem system, gravimetric reference method, uncertainty budget, ultrafine particles.

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Motor vehicles are a major source of gaseous and particulate matter pollution in urban areas, particularly of ultrafine sized particles (diameters < 0.1 µm). Exposure to particulate matter has been found to be associated with serious health effects, including respiratory and cardiovascular disease, and mortality. Particle emissions generated by motor vehicles span a very broad size range (from around 0.003-10 µm) and are measured as different subsets of particle mass concentrations or particle number count. However, there exist scientific challenges in analysing and interpreting the large data sets on motor vehicle emission factors, and no understanding is available of the application of different particle metrics as a basis for air quality regulation. To date a comprehensive inventory covering the broad size range of particles emitted by motor vehicles, and which includes particle number, does not exist anywhere in the world. This thesis covers research related to four important and interrelated aspects pertaining to particulate matter generated by motor vehicle fleets. These include the derivation of suitable particle emission factors for use in transport modelling and health impact assessments; quantification of motor vehicle particle emission inventories; investigation of the particle characteristic modality within particle size distributions as a potential for developing air quality regulation; and review and synthesis of current knowledge on ultrafine particles as it relates to motor vehicles; and the application of these aspects to the quantification, control and management of motor vehicle particle emissions. In order to quantify emissions in terms of a comprehensive inventory, which covers the full size range of particles emitted by motor vehicle fleets, it was necessary to derive a suitable set of particle emission factors for different vehicle and road type combinations for particle number, particle volume, PM1, PM2.5 and PM1 (mass concentration of particles with aerodynamic diameters < 1 µm, < 2.5 µm and < 10 µm respectively). The very large data set of emission factors analysed in this study were sourced from measurement studies conducted in developed countries, and hence the derived set of emission factors are suitable for preparing inventories in other urban regions of the developed world. These emission factors are particularly useful for regions with a lack of measurement data to derive emission factors, or where experimental data are available but are of insufficient scope. The comprehensive particle emissions inventory presented in this thesis is the first published inventory of tailpipe particle emissions prepared for a motor vehicle fleet, and included the quantification of particle emissions covering the full size range of particles emitted by vehicles, based on measurement data. The inventory quantified particle emissions measured in terms of particle number and different particle mass size fractions. It was developed for the urban South-East Queensland fleet in Australia, and included testing the particle emission implications of future scenarios for different passenger and freight travel demand. The thesis also presents evidence of the usefulness of examining modality within particle size distributions as a basis for developing air quality regulations; and finds evidence to support the relevance of introducing a new PM1 mass ambient air quality standard for the majority of environments worldwide. The study found that a combination of PM1 and PM10 standards are likely to be a more discerning and suitable set of ambient air quality standards for controlling particles emitted from combustion and mechanically-generated sources, such as motor vehicles, than the current mass standards of PM2.5 and PM10. The study also reviewed and synthesized existing knowledge on ultrafine particles, with a specific focus on those originating from motor vehicles. It found that motor vehicles are significant contributors to both air pollution and ultrafine particles in urban areas, and that a standardized measurement procedure is not currently available for ultrafine particles. The review found discrepancies exist between outcomes of instrumentation used to measure ultrafine particles; that few data is available on ultrafine particle chemistry and composition, long term monitoring; characterization of their spatial and temporal distribution in urban areas; and that no inventories for particle number are available for motor vehicle fleets. This knowledge is critical for epidemiological studies and exposure-response assessment. Conclusions from this review included the recommendation that ultrafine particles in populated urban areas be considered a likely target for future air quality regulation based on particle number, due to their potential impacts on the environment. The research in this PhD thesis successfully integrated the elements needed to quantify and manage motor vehicle fleet emissions, and its novelty relates to the combining of expertise from two distinctly separate disciplines - from aerosol science and transport modelling. The new knowledge and concepts developed in this PhD research provide never before available data and methods which can be used to develop comprehensive, size-resolved inventories of motor vehicle particle emissions, and air quality regulations to control particle emissions to protect the health and well-being of current and future generations.

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Recently published studies not only demonstrated that laser printers are often significant sources of ultrafine particles, but they also shed light on particle formation mechanisms. While the role of fuser roller temperature as a factor affecting particle formation rate has been postulated, its impact has never been quantified. To address this gap in knowledge, this study measured emissions from 30 laser printers in chamber using a standardized printing sequence, as well as monitoring fuser roller temperature. Based on a simplified mass balance equation, the average emission rates of particle number, PM2.5 and O3 were calculated. The results showed that: almost all printers were found to be high particle number emitters (i.e. > 1.01×1010 particles/min); colour printing generated more PM2.5 than monochrome printing; and all printers generated significant amounts of O3. Particle number emissions varied significantly during printing and followed the cycle of fuser roller temperature variation, which points to temperature being the strongest factor controlling emissions. For two sub-groups of printers using the same technology (heating lamps), systematic positive correlations, in the form of a power law, were found between average particle number emission rate and average roller temperature. Other factors, such as fuser material and structure, are also thought to play a role, since no such correlation was found for the remaining two sub-groups of printers using heating lamps, or for the printers using heating strips. In addition, O3 and total PM2.5 were not found to be statistically correlated with fuser temperature.

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Dust emissions from large-scale, tunnel-ventilated poultry sheds could have negative health and environmental impacts. Despite this fact, the literature concerning dust emissions from tunnel-ventilated poultry sheds in Australia and overseas is relatively scarce. Dust measurements were conducted during two consecutive production cycles at a single broiler shed on a poultry farm near Ipswich, Queensland. Fresh litter was employed during the first cycle and partially reused litter was employed during the second cycle. This provided an opportunity to study the effect that partial litter reuse has on dust emissions. Dust levels were characterised by the number concentration of suspended particles having diameter between 0.5–20 μm and by the mass concentration of dust particles below 10 μm diameter (PM10) and 2.5 μm diameter (PM2.5). In addition, we measured the number size distributions of dust particles. The average concentration and emission rate of dust was higher when partially reused litter was used in the shed than when fresh litter was used. In addition we found that dust particles emitted from the shed with partially reused litter were finer than the particles emitted with fresh litter. Although the change in litter properties is certainly contributing to this observed variability, other factors such as ventilation rate and litter moisture content are also likely to be involved.

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Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.

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The multi-criteria decision making methods, Preference METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site > urban site > roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8 ± 8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region.

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Airborne fine particles were collected at a suburban site in Queensland, Australia between 1995 and 2003. The samples were analysed for 21 elements, and Positive Matrix Factorisation (PMF), Preference Ranking Organisation METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) were applied to the data. PROMETHEE provided information on the ranking of pollutant levels from the sampling years while PMF provided insights into the sources of the pollutants, their chemical composition, most likely locations and relative contribution to the levels of particulate pollution at the site. PROMETHEE and GAIA found that the removal of lead from fuel in the area had a significant impact on the pollution patterns while PMF identified 6 pollution sources including: Railways (5.5%), Biomass Burning (43.3%), Soil (9.2%), Sea Salt (15.6%), Aged Sea Salt (24.4%) and Motor Vehicles (2.0%). Thus the results gave information that can assist in the formulation of mitigation measures for air pollution.

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Particle number concentrations and size distributions, visibility and particulate mass concentrations and weather parameters were monitored in Brisbane, Australia, on 23 September 2009, during the passage of a dust storm that originated 1400 km away in the dry continental interior. The dust concentration peaked at about mid-day when the hourly average PM2.5 and PM10 values reached 814 and 6460 µg m-3, respectively, with a sharp drop in atmospheric visibility. A linear regression analysis showed a good correlation between the coefficient of light scattering by particles (Bsp) and both PM10 and PM2.5. The particle number in the size range 0.5-20 µm exhibited a lognormal size distribution with modal and geometrical mean diameters of 1.6 and 1.9 µm, respectively. The modal mass was around 10 µm with less than 10% of the mass carried by particles smaller than 2.5 µm. The PM10 fraction accounted for about 68% of the total mass. By mid-day, as the dust began to increase sharply, the ultrafine particle number concentration fell from about 6x103 cm-3 to 3x103 cm-3 and then continued to decrease to less than 1x103 cm-3 by 14h, showing a power-law decrease with Bsp with an R2 value of 0.77 (p<0.01). Ultrafine particle size distributions also showed a significant decrease in number during the dust storm. This is the first scientific study of particle size distributions in an Australian dust storm.