Particle number and mass emission factors from combustion of wood samples collected from Queensland forest

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.

Comparison of ultrafine particle release from hardcopy devices in emission test chambers and office rooms

The release of ultrafine particles (UFP) from laser printers and office equipment was analyzed using a particle counter (FMPS; Fast Mobility Particle Sizer) with a high time resolution, as well as the appropriate mathematical models. Measurements were carried out in a 1 m³ chamber, a 24 m³ chamber and an office. The time-dependent emission rates were calculated for these environments using a deconvolution model, after which the total amount of emitted particles was calculated. The total amounts of released particles were found to be independent of the environmental parameters and therefore, in principle, they were appropriate for the comparison of different printers. On the basis of the time-dependent emission rates, “initial burst” emitters and constant emitters could also be distinguished. In the case of an “initial burst” emitter, the comparison to other devices is generally affected by strong variations between individual measurements. When conducting exposure assessments for UFP in an office, the spatial distribution of the particles also had to be considered. In this work, the spatial distribution was predicted on a case by case basis, using CFD simulation.

Comparison of emission rate values for odour and odorous chemicals derived from two sampling devices

Field and laboratory measurements identified a complex relationship between odour emission rates provided by the US EPA dynamic emission chamber and the University of New South Wales wind tunnel. Using a range of model compounds in an aqueous odour source, we demonstrate that emission rates derived from the wind tunnel and flux chamber are a function of the solubility of the materials being emitted, the concentrations of the materials within the liquid; and the aerodynamic conditions within the device – either velocity in the wind tunnel, or flushing rate for the flux chamber. The ratio of wind tunnel to flux chamber odour emission rates (OU m-2 s) ranged from about 60:1 to 112:1. The emission rates of the model odorants varied from about 40:1 to over 600:1. These results may provide, for the first time, a basis for the development of a model allowing an odour emission rate derived from either device to be used for odour dispersion modelling.

Infrared and infrared emission spectroscopy of gallium oxide α-GaO(OH) nanostructures

Infrared spectroscopy has been used to study nano to micro sized gallium oxyhydroxide α-GaO(OH), prepared using a low temperature hydrothermal route. Rod-like α-GaO(OH) crystals with average length of ~2.5 μm and width of 1.5 μm were prepared when the initial molar ratio of Ga to OH was 1:3. β-Ga2O3 nano and micro-rods were prepared through the calcination of α-GaO(OH) The initial morphology of α-GaO(OH) is retained in the β-Ga2O3 nanorods. The combination of infrared and infrared emission spectroscopy complimented with dynamic thermal analysis were used to characterise the α-GaO(OH) nanotubes and the formation of β-Ga2O3 nanorods. Bands at around 2903 and 2836 cm-1 are assigned to the -OH stretching vibration of α-GaO(OH) nanorods. Infrared bands at around 952 and 1026 cm-1 are assigned to the Ga-OH deformation modes of α-GaO(OH). A significant number of bands are observed in the 620 to 725 cm-1 region and are assigned to GaO stretching vibrations.

Source location of acoustic emission waves for structural health monitoring of bridges

The process of structural health monitoring (SHM) involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures and acoustic emission (AE) is one technique that is finding an increasing use. Acoustic emission waves are the stress waves generated by the mechanical deformation of materials. AE waves produced inside a structure can be recorded by means of sensors attached on the surface. Analysis of these recorded signals can locate and assess the extent of damage. This paper describes preliminary studies on the application of AE technique for health monitoring of bridge structures. Crack initiation or structural damage will result in wave propagation in solid and this can take place in various forms. Propagation of these waves is likely to be affected by the dimensions, surface properties and shape of the specimen. This, in turn, will affect source localization. Various laboratory test results will be presented on source localization, using pencil lead break tests. The results from the tests can be expected to aid in enhancement of knowledge of acoustic emission process and development of effective bridge structure diagnostics system.

Structural health monitoring of bridges using acoustic emission technology and signal processing techniques

Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.

Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC—a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices—thus, supporting the PCA approach.

Particle emission factors during cooking activities

Exposure to particles emitted by cooking activities may be responsible for a variety of respiratory health effects. However, the relationship between these exposures and their subsequent effects on health cannot be evaluated without understanding the properties of the emitted aerosol or the main parameters that influence particle emissions during cooking. Whilst traffic-related emissions, stack emissions and ultrafine particle concentrations (UFP, diameter < 100 nm) in urban ambient air have been widely investigated for many years, indoor exposure to UFPs is a relatively new field and in order to evaluate indoor UFP emissions accurately, it is vital to improve scientific understanding of the main parameters that influence particle number, surface area and mass emissions. The main purpose of this study was to characterise the particle emissions produced during grilling and frying as a function of the food, source, cooking temperature and type of oil. Emission factors, along with particle number concentrations and size distributions were determined in the size range 0.006-20 m using a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS). An infrared camera was used to measure the temperature field. Overall, increased emission factors were observed to be a function of increased cooking temperatures. Cooking fatty foods also produced higher particle emission factors than vegetables, mainly in terms of mass concentration, and particle emission factors also varied significantly according to the type of oil used.

Structural health monitoring of bridges using acoustic emission technology

Bridges are an important part of society's infrastructure and reliable methods are necessary to monitor them and ensure their safety and efficiency. Bridges deteriorate with age and early detection of damage helps in prolonging the lives and prevent catastrophic failures. Most bridges still in used today were built decades ago and are now subjected to changes in load patterns, which can cause localized distress and if not corrected can result in bridge failure. In the past, monitoring of structures was usually done by means of visual inspection and tapping of the structures using a small hammer. Recent advancements of sensors and information technologies have resulted in new ways of monitoring the performance of structures. This paper briefly describes the current technologies used in bridge structures condition monitoring with its prime focus in the application of acoustic emission (AE) technology in the monitoring of bridge structures and its challenges.

Investigation of mechanisms governing emission of odorants

The literature identifies several models that describe inter-phase mass transfer, key to the emission process. While the emission process is complex and these models may be more or less successful at predicting mass transfer rates, they identify three key variables for a system involving a liquid and an air phase in contact with it: • A concentration (or partial pressure) gradient driving force; • The fluid dynamic characteristics within the liquid and air phases, and • The chemical properties of the individual components within the system. In three applied research projects conducted prior to this study, samples collected with two well-known sampling devices resulted in very different odour emission rates. It was not possible to adequately explain the differences observed. It appeared likely, however, that the sample collection device might have artefact effects on the emission of odorants, i.e. the sampling device appeared to have altered the mass transfer process. This raised the obvious question: Where two different emission rates are reported for a single source (differing only in the selection of sampling device), and a credible explanation for the difference in emission rate cannot be provided, which emission rate is correct? This research project aimed to identify the factors that determine odour emission rates, the impact that the characteristics of a sampling device may exert on the key mass transfer variables, and ultimately, the impact of the sampling device on the emission rate itself. To meet these objectives, a series of targeted reviews, and laboratory and field investigations, were conducted. Two widely-used, representative devices were chosen to investigate the influence of various parameters on the emission process. These investigations provided insight into the odour emission process generally, and the influence of the sampling device specifically.

Nitrogen fertilizer rate management as a nitrous oxide mitigation strategy: Development of a nitrous oxide emission reduction protocol (NERP)

Nitrous oxide (N2O) is a potent agricultural greenhouse gas (GHG). More than 50% of the global anthropogenic N2O flux is attributable to emissions from soil, primarily due to large fertilizer nitrogen (N) applications to corn and other non-leguminous crops. Quantification of the trade–offs between N2O emissions, fertilizer N rate, and crop yield is an essential requirement for informing management strategies aiming to reduce the agricultural sector GHG burden, without compromising productivity and producer livelihood. There is currently great interest in developing and implementing agricultural GHG reduction offset projects for inclusion within carbon offset markets. Nitrous oxide, with a global warming potential (GWP) of 298, is a major target for these endeavours due to the high payback associated with its emission prevention. In this paper we use robust quantitative relationships between fertilizer N rate and N2O emissions, along with a recently developed approach for determining economically profitable N rates for optimized crop yield, to propose a simple, transparent, and robust N2O emission reduction protocol (NERP) for generating agricultural GHG emission reduction credits. This NERP has the advantage of providing an economic and environmental incentive for producers and other stakeholders, necessary requirements in the implementation of agricultural offset projects.

Identification of acoustic emission wave modes for accurate source location in plate-like structures

Acoustic emission (AE) technique is a popular tool used for structural health monitoring of civil, mechanical and aerospace structures. It is a non-destructive method based on rapid release of energy within a material by crack initiation or growth in the form of stress waves. Recording of these waves by means of sensors and subsequent analysis of the recorded signals convey information about the nature of the source. Ability to locate the source of stress waves is an important advantage of AE technique; but as AE waves travel in various modes and may undergo mode conversions, understanding of the modes (‘modal analysis’) is often necessary in order to determine source location accurately. This paper presents results of experiments aimed at finding locations of artificial AE sources on a thin plate and identifying wave modes in the recorded signal waveforms. Different source locating techniques will be investigated and importance of wave mode identification will be explored.

Influence of iodine value on combustion and NOx emission characteristics of a DI diesel engine

Biodiesel is a renewable fuel that has been shown to reduce many exhaust emissions, except oxides of nitrogen (NOx), in diesel engine cars. This is of special concern in inner urban areas that are subject to strict environmental regulations, such as EURO norms. Also, the use of pure biodiesel (B100) is inhibited because of its higher NOx emissions compared to petroleum diesel fuel. The aim of this present work is to investigate the effect of the iodine value and cetane number of various biodiesel fuels obtained from different feed stocks on the combustion and NOx emission characteristics of a direct injection (DI) diesel engine. The biodiesel fuels were chosen from various feed stocks such as coconut, palm kernel, mahua (Madhuca indica), pongamia pinnata, jatropha curcas, rice bran, and sesame seed oils. The experimental results show an approximately linear relationship between iodine value and NOx emissions. The biodiesels obtained from coconut and palm kernel showed lower NOx levels than diesel, but other biodiesels showed an increase in NOx. It was observed that the nature of the fatty acids of the biodiesel fuels had a significant influence on the NOx emissions. Also, the cetane numbers of the biodiesel fuels are affected both premixed combustion and the combustion rate, which further affected the amount of NOx formation. It was concluded that NOx emissions are influenced by many parameters of biodiesel fuels, particularly the iodine value and cetane number.