Influences of biodiesel chemical compositions and physical properties on engine exhaust particle emissions

This thesis presents a comprehensive study on the influences of biodiesel chemical composition and physical properties on diesel engine exhaust particle emissions. It examines biodiesels from several feedstocks having wide variations in their chemical composition (carbon chain length, unsaturation and oxygen content) and physical properties (density, viscosity, surface tension, boiling point etc.), and evaluates their influence on exhaust particle emissions. The outcome of this thesis is significant since it reveals the importance of regulating biodiesels chemical composition in order to ensure lowest possible emissions with better overall performance.

Comparison of charged nanoparticle concentrations near busy roads and overhead high-voltage power lines

Overhead high-voltage power lines are known sources of corona ions. These ions rapidly attach to aerosols to form charged particles in the environment. Although the effect of ions and charged particles on human health is largely unknown, much attention has focused on the increasing exposure as a result of the expanding power network in urban residential areas. However, it is not widely known that a large number of charged particles in urban environments originate from motor vehicle emissions. In this study, for the first time, we compare the concentrations of charged nanoparticles near busy roads and overhead power lines. We show that large concentrations of both positive and negative charged nanoparticles are present near busy roadways and that these concentrations commonly exceed those under high-voltage power lines. We estimate that the concentration of charged nanoparticles found near two freeways carrying around 120 vehicles per minute exceeded the corresponding maximum concentrations under two corona-emitting overhead power lines by as much as a factor of 5. The difference was most pronounced when a significant fraction of traffic consisted of heavy-duty diesel vehicles which typically have high particle and charge emission rates.

Generalised features for bird vocalisation retrieval in acoustic recordings

Bioacoustic monitoring has become a significant research topic for species diversity conservation. Due to the development of sensing techniques, acoustic sensors are widely deployed in the field to record animal sounds over a large spatial and temporal scale. With large volumes of collected audio data, it is essential to develop semi-automatic or automatic techniques to analyse the data. This can help ecologists make decisions on how to protect and promote the species diversity. This paper presents generic features to characterize a range of bird species for vocalisation retrieval. In the implementation, audio recordings are first converted to spectrograms using short-time Fourier transform, then a ridge detection method is applied to the spectrogram for detecting points of interest. Based on the detected points, a new region representation are explored for describing various bird vocalisations and a local descriptor including temporal entropy, frequency bin entropy and histogram of counts of four ridge directions is calculated for each sub-region. To speed up the retrieval process, indexing is carried out and the retrieved results are ranked according to similarity scores. The experiment results show that our proposed feature set can achieve 0.71 in term of retrieval success rate which outperforms spectral ridge features alone (0.55) and Mel frequency cepstral coefficients (0.36).

Clustering acoustic events in environmental recordings for species richness surveys

Environmental acoustic recordings can be used to perform avian species richness surveys, whereby a trained ornithologist can observe the species present by listening to the recording. This could be made more efficient by using computational methods for iteratively selecting the richest parts of a long recording for the human observer to listen to, a process known as “smart sampling”. This allows scaling up to much larger ecological datasets. In this paper we explore computational approaches based on information and diversity of selected samples. We propose to use an event detection algorithm to estimate the amount of information present in each sample. We further propose to cluster the detected events for a better estimate of this amount of information. Additionally, we present a time dispersal approach to estimating diversity between iteratively selected samples. Combinations of approaches were evaluated on seven 24-hour recordings that have been manually labeled by bird watchers. The results show that on average all the methods we have explored would allow annotators to observe more new species in fewer minutes compared to a baseline of random sampling at dawn.

Metrological assessment of a portable analyzer for monitoring the particle size distribution of ultrafine particles

Adverse health effects caused by worker exposure to ultrafine particles have been detected in recent years. The scientific community focuses on the assessment of ultrafine aerosols in different microenvironments in order to determine the related worker exposure/dose levels. To this end, particle size distribution measurements have to be taken along with total particle number concentrations. The latter are obtainable through hand-held monitors. A portable particle size distribution analyzer (Nanoscan SMPS 3910, TSI Inc.) was recently commercialized, but so far no metrological assessment has been performed to characterize its performance with respect to well-established laboratory- based instruments such as the scanning mobility particle sizer (SMPS) spectrometer. The present paper compares the aerosol monitoring capability of the Nanoscan SMPS to the laboratory SMPS in order to evaluate whether the Nanoscan SMPS is suitable for field experiments designed to characterize particle exposure in different microenvironments. Tests were performed both in a Marple calm air chamber, where fresh diesel particulate matter and atomized dioctyl phthalate particles were monitored, and in microenvironments, where outdoor, urban, indoor aged, and indoor fresh aerosols were measured. Results show that the Nanoscan SMPS is able to properly measure the particle size distribution for each type of aerosol investigated, but it overestimates the total particle number concentration in the case of fresh aerosols. In particular, the test performed in the Marple chamber showed total concentrations up to twice those measured by the laboratory SMPS—likely because of the inability of the Nanoscan SMPS unipolar charger to properly charge aerosols made up of aggregated particles. Based on these findings, when field test exposure studies are conducted, the Nanoscan SMPS should be used in tandem

Particle emissions from biodiesels with different physical properties and chemical composition

Biodiesels produced from different feedstocks usually have wide variations in their fatty acid methyl ester (FAME) so that their physical properties and chemical composition are also different. The aim of this study is to investigate the effect of the physical properties and chemical composition of biodiesels on engine exhaust particle emissions. Alongside with neat diesel, four biodiesels with variations in carbon chain length and degree of unsaturation have been used at three blending ratios (B100, B50, B20) in a common rail engine. It is found that particle emission increased with the increase of carbon chain length. However, for similar carbon chain length, particle emissions from biodiesel having relatively high average unsaturation are found to be slightly less than that of low average unsaturation. Particle size is also found to be dependent on fuel type. The fuel or fuel mix responsible for higher particle mass (PM) and particle number (PN) emissions is also found responsible for larger particle median size. Particle emissions reduced consistently with fuel oxygen content regardless of the proportion of biodiesel in the blends, whereas it increased with fuel viscosity and surface tension only for higher diesel–biodiesel blend percentages (B100, B50). However, since fuel oxygen content increases with the decreasing carbon chain length, it is not clear which of these factors drives the lower particle emission. Overall, it is evident from the results presented here that chemical composition of biodiesel is more important than its physical properties in controlling exhaust particle emissions.

Development of non-intrusive monitoring for reactive switching of high voltage circuit breaker

High-voltage circuit breakers are among the most important equipments for ensuring the efficient and safe operation of an electric power system. On occasion, circuit breaker operators may wish to check whether equipment is performing satisfactorily and whether controlled switching systems are producing reliable and repeatable stress control. Monitoring of voltage and current waveforms during switching using established methods will provide information about the magnitude and frequency of voltage transients as a result of re-ignitions and restrikes. However, high frequency waveform measurement requires shutdown of circuit breaker and use of specialized equipment. Two utilities, Hydro-Québec in Canada and Powerlink Queensland in Australia, have been working on the development and application of a non-intrusive, cost-effective and flexible diagnostic system for monitoring high-voltage circuit breakers for reactive switching. The proposed diagnostic approach relies on the non-intrusive assessment of key parameters such as operating times, prestrike characteristics, re-ignition and restrike detection. Transient electromagnetic emissions have been identified as a promising means to evaluate the abovementioned parameters non-intrusively. This paper describes two complimentary methods developed concurrently by Powerlink and Hydro-Québec. Also, return of experiences on the application to capacitor bank and shunt reactor switching is presented.

Visual fingerprints of the acoustic environment: The use of acoustic indices to characterise natural habitats

Acoustic recordings play an increasingly important role in monitoring terrestrial environments. However, due to rapid advances in technology, ecologists are accumulating more audio than they can listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings by calculating acoustic indices. These are statistics which describe the temporal-spectral distribution of acoustic energy and reflect content of ecological interest. We combine spectral indices to produce false-color spectrogram images. These not only reveal acoustic content but also facilitate navigation. An additional analytic challenge is to find appropriate descriptors to summarize the content of 24-hour recordings, so that it becomes possible to monitor long-term changes in the acoustic environment at a single location and to compare the acoustic environments of different locations. We describe a 24-hour ‘acoustic-fingerprint’ which shows some preliminary promise.

Removal of organic content from diesel exhaust particles alters cellular responses of primary human bronchial epithelial cells cultured at an air-liquid interface

Background Exposure to air pollutants, including diesel particulate matter, has been linked to adverse respiratory health effects. Inhaled diesel particulate matter contains adsorbed organic compounds. It is not clear whether the adsorbed organics or the residual components are more deleterious to airway cells. Using a physiologically relevant model, we investigated the role of diesel organic content on mediating cellular responses of primary human bronchial epithelial cells (HBECs) cultured at an air-liquid interface (ALI). Methods Primary HBECs were cultured and differentiated at ALI for at least 28 days. To determine which component is most harmful, we compared primary HBEC responses elicited by residual (with organics removed) diesel emissions (DE) to those elicited by neat (unmodified) DE for 30 and 60 minutes at ALI, with cigarette smoke condensate (CSC) as the positive control, and filtered air as negative control. Cell viability (WST-1 cell proliferation assay), inflammation (TNF-α, IL-6 and IL-8 ELISA) and changes in gene expression (qRT-PCR for HO-1, CYP1A1, TNF-α and IL-8 mRNA) were measured. Results Immunofluorescence and cytological staining confirmed the mucociliary phenotype of primary HBECs differentiated at ALI. Neat DE caused a comparable reduction in cell viability at 30 or 60 min exposures, whereas residual DE caused a greater reduction at 60 min. When corrected for cell viability, cytokine protein secretion for TNF-α, IL-6 and IL-8 were maximal with residual DE at 60 min. mRNA expression for HO-1, CYP1A1, TNF-α and IL-8 was not significantly different between exposures. Conclusion This study provides new insights into epithelial cell responses to diesel emissions using a physiologically relevant aerosol exposure model. Both the organic content and residual components of diesel emissions play an important role in determining bronchial epithelial cell response in vitro. Future studies should be directed at testing potentially useful interventions against the adverse health effects of air pollution exposure.

Helium Gas Purity Monitor based on Low Frequency Acoustic Resonance

Monitoring gas purity is an important aspect of gas recovery stations where air is usually one of the major impurities. Purity monitors of Katherometric type ate commercially available for this purpose. Alternatively, we discuss here a helium gas purity monitor based on acoustic resonance of a cavity at audio frequencies. It measures the purity by monitoring the resonant frequency of a cylindrical cavity filled with the gas under test and excited by conventional telephone transducers fixed at the ends. The use of the latter simplifies the design considerably. The paper discusses the details of the resonant cavity and the electronic circuit along with temperature compensation. The unit has been calibrated with helium gas of known purities. The unit has a response time of the order of 10 minutes and measures the gas purity to an accuracy of 0.02%. The unit has been installed in our helium recovery system and is found to perform satisfactorily.

Compact features for birdcall retrieval from environmental acoustic recordings

Bioacoustic data can be used for monitoring animal species diversity. The deployment of acoustic sensors enables acoustic monitoring at large temporal and spatial scales. We describe a content-based birdcall retrieval algorithm for the exploration of large data bases of acoustic recordings. In the algorithm, an event-based searching scheme and compact features are developed. In detail, ridge events are detected from audio files using event detection on spectral ridges. Then event alignment is used to search through audio files to locate candidate instances. A similarity measure is then applied to dimension-reduced spectral ridge feature vectors. The event-based searching method processes a smaller list of instances for faster retrieval. The experimental results demonstrate that our features achieve better success rate than existing methods and the feature dimension is greatly reduced.

Implementation of an electronic nose for continuous odour monitoring in a poultry shed

Continuous odour monitoring technologies are necessary to understand the complex odour-generating mechanisms within poultry housing as well as to identify strategies to reduce the impact of odour emissions on local communities. To evaluate electronic nose (EN) technologies for continuously assessing odour concentration in poultry housing, a mobile laboratory containing an electronic nose and an associated sample delivery system was deployed to a commercial poultry farm and tested over a broiler production cycle. The results demonstrated that it was possible to develop a model to allow an electronic nose to provide a semi-continuous measurement of odour concentrations. The electronic nose was also able to demonstrate the influence of shed conditions on odour emissions.

Process studies of odour emissions from effluent ponds using machine-based odour measurement

Replicable experimental studies using a novel experimental facility and a machine-based odour quantification technique were conducted to demonstrate the relationship between odour emission rates and pond loading rates. The odour quantification technique consisted of an electronic nose, AromaScan A32S, and an artificial neural network. Odour concentrations determined by olfactometry were used along with the AromaScan responses to train the artificial neural network. The trained network was able to predict the odour emission rates for the test data with a correlation coefficient of 0.98. Time averaged odour emission rates predicted by the machine-based odour quantification technique, were strongly correlated with volatile solids loading rate, demonstrating the increased magnitude of emissions from a heavily loaded effluent pond. However, it was not possible to obtain the same relationship between volatile solids loading rates and odour emission rates from the individual data. It is concluded that taking a limited number of odour samples over a short period is unlikely to provide a representative rate of odour emissions from an effluent pond. A continuous odour monitoring instrument will be required for that more demanding task.

Pitch discrimination in optimal and suboptimal acoustic environments: electroencephalographic, magnetoencephalographic, and behavioral evidence

Pitch discrimination is a fundamental property of the human auditory system. Our understanding of pitch-discrimination mechanisms is important from both theoretical and clinical perspectives. The discrimination of spectrally complex sounds is crucial in the processing of music and speech. Current methods of cognitive neuroscience can track the brain processes underlying sound processing either with precise temporal (EEG and MEG) or spatial resolution (PET and fMRI). A combination of different techniques is therefore required in contemporary auditory research. One of the problems in comparing the EEG/MEG and fMRI methods, however, is the fMRI acoustic noise. In the present thesis, EEG and MEG in combination with behavioral techniques were used, first, to define the ERP correlates of automatic pitch discrimination across a wide frequency range in adults and neonates and, second, they were used to determine the effect of recorded acoustic fMRI noise on those adult ERP and ERF correlates during passive and active pitch discrimination. Pure tones and complex 3-harmonic sounds served as stimuli in the oddball and matching-to-sample paradigms. The results suggest that pitch discrimination in adults, as reflected by MMN latency, is most accurate in the 1000-2000 Hz frequency range, and that pitch discrimination is facilitated further by adding harmonics to the fundamental frequency. Newborn infants are able to discriminate a 20% frequency change in the 250-4000 Hz frequency range, whereas the discrimination of a 5% frequency change was unconfirmed. Furthermore, the effect of the fMRI gradient noise on the automatic processing of pitch change was more prominent for tones with frequencies exceeding 500 Hz, overlapping with the spectral maximum of the noise. When the fundamental frequency of the tones was lower than the spectral maximum of the noise, fMRI noise had no effect on MMN and P3a, whereas the noise delayed and suppressed N1 and exogenous N2. Noise also suppressed the N1 amplitude in a matching-to-sample working memory task. However, the task-related difference observed in the N1 component, suggesting a functional dissociation between the processing of spatial and non-spatial auditory information, was partially preserved in the noise condition. Noise hampered feature coding mechanisms more than it hampered the mechanisms of change detection, involuntary attention, and the segregation of the spatial and non-spatial domains of working-memory. The data presented in the thesis can be used to develop clinical ERP-based frequency-discrimination protocols and combined EEG and fMRI experimental paradigms.

Mobile assessment of on-road air pollution and its sources along the East-West Highway in Bhutan

Human exposures in transportation microenvironments are poorly represented by ambient stationary monitoring. A number of on-road studies using vehicle-based mobile monitoring have been conducted to address this. Most previous studies were conducted on urban roads in developed countries where the primary emission source was vehicles. Few studies have examined on-road pollution in developing countries in urban settings. Currently, no study has been conducted for roadways in rural environments where a substantial proportion of the population live. This study aimed to characterize on-road air quality on the East-West Highway (EWH) in Bhutan and identify its principal sources. We conducted six mobile measurements of PM10, particle number (PN) count and CO along the entire 570 km length of the EWH. We divided the EWH into five segments, R1-R5, taking the road length between two district towns as a single road segment. The pollutant concentrations varied widely along the different road segments, with the highest concentrations for R5 compared with other road segments (PM10 = 149 µg/m3, PN = 5.74 × 104 particles/cm-3, CO = 0.19 ppm), which is the final segment of the road to the capital. Apart from vehicle emissions, the dominant sources were road works, unpaved roads and roadside combustion activities. Overall, the highest contributions above the background levels were made by unpaved roads for PM10 (6 times background), and vehicle emissions for PN and CO (5 and 15 times background, respectively). Notwithstanding the differences in instrumentation used and particle size range measured, the current study showed lower PN concentrations compared with similar on-road studies. However, concentrations were still high enough that commuters, road maintenance workers and residents living along the EWH, were potentially exposed to elevated pollutant concentrations from combustion and non-combustion sources. Future studies should focus on assessing the dispersion patterns of roadway pollutants and defining the short- and long-term health impacts of exposure in Bhutan, as well as in other developing countries with similar characteristics.