958 resultados para Biomass Burning


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Atmospheric particulate matter (PM) is genotoxic and recently was classified as carcinogenic to humans by the International Agency for Research on Cancer. PM chemical composition varies depending on source and atmospheric conditions. The Salmonella/microsome assay is the most used mutagenicity test and can identify the major chemical classes responsible for observed mutagenicity. The objective of this work was to characterize the mutagenicity of PM samples from a countryside city, Limeira, Brazil, which is influenced by heavy traffic and sugar cane biomass burning. Six samples of total PM were collected. Air mass backward trajectories were calculated. Organic extracts were assayed using the Salmonella/microsome microsuspension mutagenicity assay using TA98, YG1041, and TA1538, with and without metabolic activation (S9). YG1041 was the most sensitive strain and mutagenicity reached 9,700 revertants per m(3) without metabolic activation. Potency for TA1538 was higher than TA98, indicating that this strain should be considered in air mutagenicity studies. The increased response to YG1041 relative to TA98, and the decreased response with S9, suggests that nitroaromatics are the major contributors. Limeira is among the most mutagenic cities in the world. High mutagenicity in Limeira seems to occur when the air mass from the area of sugarcane production is mixed with air from the region impacted by anthropogenic activities such as traffic. An increase in the formation of nitro-polycyclic aromatic hydrocarbons may result from longer contact time between the aromatic compounds and the atmosphere with high NOx and ozone concentration, although more studies are required to confirm this hypothesis. Environ. Mol. Mutagen., 2015. © 2015 Wiley Periodicals, Inc.

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One of the energy alternatives that provide utility, flexibility, cleanliness and economy is biomass, such as forest waste (wood) and agricultural (sugarcane bagasse, rice husks, coffee pods, etc.). However, with its increasing supply and use grows also the concern of industries to invest in monitoring and control of emissions into the atmosphere, because during biomass burning are emitted as exhaust gases, fine particles known as particulates, which greatly contribute to the triggering of serious health problems to humans, in addition to the environmental damage. With that, this work aimed to conduct a monitoring of particulate and gaseous pollutants emissions to the atmosphere from the burning of various types of biomass used by industries. The equipment used for sampling were the optical monitor DataRAM 4 and the Unigas3000 + gas sampler. The results showed that biomass coffee pods presented the greatest concentration of particulates (485119 μg m-3) with particle diameters between 0.0602 μm and 0.3502 μm, i.e. the most ultrafine particles, harmful to human health and the environment. The largest emissions of CO and NOx were observed, respectively, for the coffee pods (3500 ppm) and for the rice husk (48 ppm). As for the superior calorific value (PCS), the best of fuel, with higher PCS, was the Eucalyptus grandis.

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The numbers of fires detected on forest, savanna and transition lands during the 2002-10 biomass burning seasons in Amazonia are shown using fire count data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). The ratio of forest fires to savanna fires has varied substantially over the study period, with a maximum ratio of 0.65:1 in 2005 and a minimum ratio of 0.27:1 in 2009, with the four lowest years occurring in 2007-10. The burning during the droughts of 2007 and 2010 is attributed to a higher number of savanna fires relative to the drought of 2005. A decrease in the regional mean single scattering albedo of biomass burning aerosols, consistent with the shift from forest to savanna burning, is also shown. During the severe drought of 2010, forest fire detections were lower in many areas compared with 2005, even though the drought was more severe in 2010. This result suggests that improved fire management practices, including stricter burning regulations as well as lower deforestation burning, may have reduced forest fires in 2010 relative to 2005 in some areas of the Amazon Basin.

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Abstract Background To determine the possible genotoxic effect of exposure to the smoke generated by biomass burning on workers involved in manual sugar cane harvesting. Methods The frequency of micronuclei in exfoliated buccal cells and peripheral blood lymphocytes was determined in sugarcane workers in the Barretos region of Brazil, during the harvest season and compared to a control population, comprised of administrative employees of Barretos Cancer Hospital. Results The frequency of micronuclei was higher in the sugar cane workers. The mean frequency in blood lymphocytes (micronuclei/1000 cells) in the test group was 8.22 versus 1.27 in the control group. The same effect was observed when exfoliated buccal cells were considered (22.75 and 9.70 micronuclei/1000 cells for sugar cane workers and controls, respectively). Conclusion Exposure to emissions produced by the burning of sugar cane during harvesting induces genomic instability in workers, indicating the necessity of adopting more advanced techniques of harvesting sugar cane to preserve human health.

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Knowledge of particle emission characteristics associated with forest fires and in general, biomass burning, is becoming increasingly important due to the impact of these emissions on human health. Of particular importance is developing a better understanding of the size distribution of particles generated from forest combustion under different environmental conditions, as well as provision of emission factors for different particle size ranges. This study was aimed at quantifying particle emission factors from four types of wood found in South East Queensland forests: Spotted Gum (Corymbia citriodora), Red Gum (Eucalypt tereticornis), Blood Gum (Eucalypt intermedia), and Iron bark (Eucalypt decorticans); under controlled laboratory conditions. The experimental set up included a modified commercial stove connected to a dilution system designed for the conditions of the study. Measurements of particle number size distribution and concentration resulting from the burning of woods with a relatively homogenous moisture content (in the range of 15 to 26 %) and for different rates of burning were performed using a TSI Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 600 nm and a TSI Dust Trak for PM2.5. The results of the study in terms of the relationship between particle number size distribution and different condition of burning for different species show that particle number emission factors and PM2.5 mass emission factors depend on the type of wood and the burning rate; fast burning or slow burning. The average particle number emission factors for fast burning conditions are in the range of 3.3 x 1015 to 5.7 x 1015 particles/kg, and for PM2.5 are in the range of 139 to 217 mg/kg.

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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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The paper presents the results of a study conducted into the relationship between dwelling characteristics and occupant activities with the respiratory health of resident women and children in Lao People’s Democratic Republic (PDR). Lao is one of the least developed countries in south-east Asia with poor life expectancies and mortality rates. The study, commissioned by the World Health Organisation, included questionnaires delivered to residents of 356 dwellings in nine districts in Lao PDR over a five month period (December 2005-April 2006), with the aim of identifying the association between respiratory health and indoor air pollution, in particular exposures related to indoor biomass burning. Adjusted odds ratios were calculated for each health outcome separately using binary logistic regression. After adjusting for age, a wide range of symptoms of respiratory illness in women and children aged 1-4 years were positively associated with a range of indoor exposures related to indoor cooking, including exposure to a fire and location of the cooking place. Among women, “dust always inside the house” and smoking were also identified as strong risk factors for respiratory illness. Other strong risk factors for children, after adjusting for age and gender, included dust and drying clothes inside. This analysis confirms the role of indoor air pollution in the burden of disease among women and children in Lao PDR.

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Carbon dioxide (CO2), as a primary product of combustion, is a known factor affecting climate change and global warming. In Australia, CO2 emissions from biomass burning are a significant contributor to total carbon in the atmosphere and therefore, it is important to quantify the CO2 emission factors from biomass burning in order to estimate their magnitude and impact on the Australian atmosphere. This paper presents the quantification of CO2 emission factors for five common tree species found in South East Queensland forests, as well as several grasses taken from savannah lands in the Northern Territory of Australia, under controlled ‘fast burning’ and ‘slow burning’ laboratory conditions. The results showed that CO2 emission factors varied according to the type of vegetation and burning conditions, with emission factors for fast burning being 2574 ± 254 g/kg for wood, 394 ± 40 g/kg for branches and leaves, and 2181 ± 120 g/kg for grass. Under slow burning conditions, the CO2 emission factors were 218 ± 20 g/kg for wood, 392± 80 g/kg for branches and leaves, and 2027 ± 809 g/kg for grass.

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Purpose: To investigate the significance of sources around measurement sites, assist the development of control strategies for the important sources and mitigate the adverse effects of air pollution due to particle size. Methods: In this study, sampling was conducted at two sites located in urban/industrial and residential areas situated at roadsides along the Brisbane Urban Corridor. Ultrafine and fine particle measurements obtained at the two sites in June-July 2002 were analysed by Positive Matrix Factorization (PMF). Results: Six sources were present, including local traffic, two traffic sources, biomass burning, and two currently unidentified sources. Secondary particles had a significant impact at Site 1, while nitrates, peak traffic hours and main roads located close to the source also affected the results for both sites. Conclusions: This significant traffic corridor exemplifies the type of sources present in heavily trafficked locations and future attempts to control pollution in this type of environment could focus on the sources that were identified.

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Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

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Long term exposure to vehicle emissions has been associated with harmful health effects. Children are amongst the most susceptible group and schools represent an environment where they can experience significant exposure to vehicle emissions. However, there are limited studies on children’s exposure to vehicle emissions in schools. The aim of this study was to quantify the concentration of organic aerosol and in particular, vehicle emissions that children are exposed to during school hours. Therefore an Aerodyne compact time-of-flight aerosol mass spectrometer (TOF-AMS) was deployed at five urban schools in Brisbane, Australia. The TOF-AMS enabled the chemical composition of the non- refractory (NR-PM1) to be analysed with a high temporal resolution to assess the concentration of vehicle emissions and other organic aerosols during school hours. At each school the organic fraction comprised the majority of NR-PM1 with secondary organic aerosols as the main constitute. At two of the schools, a significant source of the organic aerosol (OA) was slightly aged vehicle emissions from nearby highways. More aged and oxidised OA was observed at the other three schools, which also recorded strong biomass burning influences. Primary emissions were found to dominate the OA at only one school which had an O:C ratio of 0.17, due to fuel powered gardening equipment used near the TOF-AMS. The diurnal cycle of OA concentration varied between schools and was found to be at a minimum during school hours. The major organic component that school children were exposed to during school hours was secondary OA. Peak exposure of school children to HOA occurred during school drop off and pick up times. Unless a school is located near major roads, children are exposed predominately to regional secondary OA as opposed to local emissions during schools hours in urban environments.

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Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

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An Aerodyne Aerosol Mass Spectrometer was deployed at five urban schools to examine spatial and temporal variability of organic aerosols (OA) and positive matrix factorization (PMF) used for the first time in the Southern Hemisphere to apportion the sources of the OA across an urban area. The sources identified included hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and oxygenated OA (OOA). At all sites, the main source was OOA, which accounted for 62–73% of the total OA mass and was generally more oxidized compared to those reported in the Northern Hemisphere. This suggests that there are differences in aging processes or regional sources in the two hemispheres. Unlike HOA and BBOA, OOA demonstrated instructive temporal variations but not spatial variation across the urban area. Application of cluster analysis to the PMF-derived sources offered a simple and effective method for qualitative comparison of PMF sources that can be used in other studies.

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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.