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.

Infrared and infrared emission spectroscopic study of China typical kaolinite and halloysite

The structure and thermal stability between typical China kaolinite and halloysite were analysed by X-ray diffraction (XRD), infrared spectroscopy, infrared emission spectroscopy (IES) and Raman spectroscopy. Infrared emission spectroscopy over the temperature range of 300 to 700 °C has been used to characterise the thermal decomposition of both kaolinite and halloysite. Halloysite is characterised by two bands in the water bending region at 1629 and 1648 cm-1, attributed to structure water and coordinated water in the interlayer. Well defined hydroxyl stretching bands at around 3695, 3679, 3652 and 3625 cm-1 are observed for both kaolinite and halloysite. In the 550 °C infrared emission spectrum of halloysite is similar to that of kaolinite in 650-1350 cm-1 region. The infrared emission spectra of halloysite were found to be considerably different to that of kaolinite at lower temperatures. This difference is attributed to the fundamental difference in the structure of the two minerals.

Thermal analysis and infrared emission spectroscopic study of halloysite-potassium acetate intercalation compound

The thermal decomposition of halloysite-potassium acetate intercalation compound was investigated by thermogravimetric analysis and infrared emission spectroscopy. The X-ray diffraction patterns indicated that intercalation of potassium acetate into halloysite caused an increase of the basal spacing from 1.00 to 1.41 nm. The thermogravimetry results show that the mass losses of intercalation the compound occur in main three main steps, which correspond to (a) the loss of adsorbed water (b) the loss of coordination water and (c) the loss of potassium acetate and dehydroxylation. The temperature of dehydroxylation and dehydration of halloysite is decreased about 100 °C. The infrared emission spectra clearly show the decomposition and dehydroxylation of the halloysite intercalation compound when the temperature is raised. The dehydration of the intercalation compound is followed by the loss of intensity of the stretching vibration bands at region 3600-3200 cm-1. Dehydroxylation is followed by the decrease in intensity in the bands between 3695 and 3620 cm-1. Dehydration was completed by 300 °C and partial dehydroxylation by 350 °C. The inner hydroxyl group remained until around 500 °C.

Derivation of motor vehicle tailpipe particle emission factors suitable for modelling urban fleet emissions and air quality assessments

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.

Study of acoustic emission data analysis tools for structural health monitoring applications

Acoustic emission (AE) technique is one of the popular diagnostic techniques used for structural health monitoring of mechanical, aerospace and civil structures. But several challenges still exist in successful application of AE technique. This paper explores various tools for analysis of recorded AE data to address two primary challenges: discriminating spurious signals from genuine signals and devising ways to quantify damage levels.

Structural health monitoring of bridges : source localisation in acoustic emission technique

Managing the sustainability of urban infrastructure requires regular health monitoring of key infrastructure such as bridges. The process of structural health monitoring 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 is one technique that is finding an increasing use in the monitoring of civil infrastructures such as bridges. Acoustic emission technique is based on the recording of stress waves generated by rapid release of energy inside a material, followed by analysis of recorded signals to locate and identify the source of emission and assess its severity. This chapter first provides a brief background of the acoustic emission technique and the process of source localization. Results from laboratory experiments conducted to explore several aspects of the source localization process are also presented. The findings from the study can be expected to enhance knowledge of the acoustic emission process, and to aid the development of effective bridge structure diagnostics systems.

Enhancing acoustic emission signals from multi-cylinder diesel engine

This paper presents techniques which can be viewed as pre-processing step towards diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time-frequency analysis, selection of optimum frequency band. Some results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals are also outlined. The results on separation of RMS signals show this technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events.

Primary students' success on the structured number line

Number lines are part of our everyday life (e.g., thermometers, kitchen scales) and are frequently used in primary mathematics as instructional aids, in texts and for assessment purposes on mathematics tests. There are two major types of number lines; structured number lines, which are the focus of this paper, and empty number lines. Structured number lines represent mathematical information by the placement of marks on a horizontal or vertical line which has been marked into proportional segments (Figure 1). Empty number lines are blank lines which students can use for calculations (Figure 2) and are not discussed further here (see van den Heuvel-Panhuizen, 2008, on the role of empty number lines). In this article, we will focus on how students’ knowledge of the structured number line develops and how they become successful users of this mathematical tool.

Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors

This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.

Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Analysis of acoustic emission data for structural health monitoring applications

Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. It is one of the several diagnostic techniques currently used for structural health monitoring (SHM) of civil infrastructure such as bridges. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. But several challenges still exist. Due to high sampling rate required for data capture, large amount of data is generated during AE testing. This is further complicated by the presence of a number of spurious sources that can produce AE signals which can then mask desired signals. Hence, an effective data analysis strategy is needed to achieve source discrimination. This also becomes important for long term monitoring applications in order to avoid massive date overload. Analysis of frequency contents of recorded AE signals together with the use of pattern recognition algorithms are some of the advanced and promising data analysis approaches for source discrimination. This paper explores the use of various signal processing tools for analysis of experimental data, with an overall aim of finding an improved method for source identification and discrimination, with particular focus on monitoring of steel bridges.

Application of acoustic emission technology in monitoring structure integrity of bridges

Bridges are an important part of a nation’s infrastructure and reliable monitoring methods are necessary to ensure their safety and efficiency. Most bridges in use today were built decades ago and are now subjected to changes in load patterns that can cause localized distress, which can result in bridge failure if not corrected. Early detection of damage helps in prolonging lives of bridges and preventing catastrophic failures. This paper briefly reviews the various technologies currently used in health monitoring of bridge structures and in particular discusses the application and challenges of acoustic emission (AE) technology. Some of the results from laboratory experiments on a bridge model are also presented. The main objectives of these experiments are source localisation and assessment. The findings of the study can be expected to enhance the knowledge of acoustic emission process and thereby aid in the development of an effective bridge structure diagnostics system.

The ghrelin receptor isoforms (GHS-R1a and GHS-R1b) and GPR39 : an investigation into receptor dimerisation

Prostate cancer is the second most common cause of cancer-related deaths in Western males. Current diagnostic, prognostic and treatment approaches are not ideal and advanced metastatic prostate cancer is incurable. There is an urgent need for improved adjunctive therapies and markers for this disease. GPCRs are likely to play a significant role in the initiation and progression of prostate cancer. Over the last decade, it has emerged that G protein coupled receptors (GPCRs) are likely to function as homodimers and heterodimers. Heterodimerisation between GPCRs can result in the formation of novel pharmacological receptors with altered functional outcomes, and a number of GPCR heterodimers have been implicated in the pathogenesis of human disease. Importantly, novel GPCR heterodimers represent potential new targets for the development of more specific therapeutic drugs. Ghrelin is a 28 amino acid peptide hormone which has a unique n-octanoic acid post-translational modification. Ghrelin has a number of important physiological roles, including roles in appetite regulation and the stimulation of growth hormone release. The ghrelin receptor is the growth hormone secretagogue receptor type 1a, GHS-R1a, a seven transmembrane domain GPCR, and GHS-R1b is a C-terminally truncated isoform of the ghrelin receptor, consisting of five transmembrane domains. Growing evidence suggests that ghrelin and the ghrelin receptor isoforms, GHS-R1a and GHS-R1b, may have a role in the progression of a number of cancers, including prostate cancer. Previous studies by our research group have shown that the truncated ghrelin receptor isoform, GHS-R1b, is not expressed in normal prostate, however, it is expressed in prostate cancer. The altered expression of this truncated isoform may reflect a difference between a normal and cancerous state. A number of mutant GPCRs have been shown to regulate the function of their corresponding wild-type receptors. Therefore, we investigated the potential role of interactions between GHS-R1a and GHS-R1b, which are co-expressed in prostate cancer and aimed to investigate the function of this potentially new pharmacological receptor. In 2005, obestatin, a 23 amino acid C-terminally amidated peptide derived from preproghrelin was identified and was described as opposing the stimulating effects of ghrelin on appetite and food intake. GPR39, an orphan GPCR which is closely related to the ghrelin receptor, was identified as the endogenous receptor for obestatin. Recently, however, the ability of obestatin to oppose the effects of ghrelin on appetite and food intake has been questioned, and furthermore, it appears that GPR39 may in fact not be the obestatin receptor. The role of GPR39 in the prostate is of interest, however, as it is a zinc receptor. Zinc has a unique role in the biology of the prostate, where it is normally accumulated at high levels, and zinc accumulation is altered in the development of prostate malignancy. Ghrelin and zinc have important roles in prostate cancer and dimerisation of their receptors may have novel roles in malignant prostate cells. The aim of the current study, therefore, was to demonstrate the formation of GHS-R1a/GHS-R1b and GHS-R1a/GPR39 heterodimers and to investigate potential functions of these heterodimers in prostate cancer cell lines. To demonstrate dimerisation we first employed a classical co-immunoprecipitation technique. Using cells co-overexpressing FLAG- and Myc- tagged GHS-R1a, GHS-R1b and GPR39, we were able to co-immunoprecipitate these receptors. Significantly, however, the receptors formed high molecular weight aggregates. A number of questions have been raised over the propensity of GPCRs to aggregate during co-immunoprecipitation as a result of their hydrophobic nature and this may be misinterpreted as receptor dimerisation. As we observed significant receptor aggregation in this study, we used additional methods to confirm the specificity of these putative GPCR interactions. We used two different resonance energy transfer (RET) methods; bioluminescence resonance energy transfer (BRET) and fluorescence resonance energy transfer (FRET), to investigate interactions between the ghrelin receptor isoforms and GPR39. RET is the transfer of energy from a donor fluorophore to an acceptor fluorophore when they are in close proximity, and RET methods are, therefore, applicable to the observation of specific protein-protein interactions. Extensive studies using the second generation bioluminescence resonance energy transfer (BRET2) technology were performed, however, a number of technical limitations were observed. The substrate used during BRET2 studies, coelenterazine 400a, has a low quantum yield and rapid signal decay. This study highlighted the requirement for the expression of donor and acceptor tagged receptors at high levels so that a BRET ratio can be determined. After performing a number of BRET2 experimental controls, our BRET2 data did not fit the predicted results for a specific interaction between these receptors. The interactions that we observed may in fact represent ‘bystander BRET’ resulting from high levels of expression, forcing the donor and acceptor into close proximity. Our FRET studies employed two different FRET techniques, acceptor photobleaching FRET and sensitised emission FRET measured by flow cytometry. We were unable to observe any significant FRET, or FRET values that were likely to result from specific receptor dimerisation between GHS-R1a, GHS-R1b and GPR39. While we were unable to conclusively demonstrate direct dimerisation between GHS-R1a, GHS-R1b and GPR39 using several methods, our findings do not exclude the possibility that these receptors interact. We aimed to investigate if co-expression of combinations of these receptors had functional effects in prostate cancers cells. It has previously been demonstrated that ghrelin stimulates cell proliferation in prostate cancer cell lines, through ERK1/2 activation, and GPR39 can stimulate ERK1/2 signalling in response to zinc treatments. Additionally, both GHS-R1a and GPR39 display a high level of constitutive signalling and these constitutively active receptors can attenuate apoptosis when overexpressed individually in some cell types. We, therefore, investigated ERK1/2 and AKT signalling and cell survival in prostate cancer the potential modulation of these functions by dimerisation between GHS-R1a, GHS-R1b and GPR39. Expression of these receptors in the PC-3 prostate cancer cell line, either alone or in combination, did not alter constitutive ERK1/2 or AKT signalling, basal apoptosis or tunicamycin-stimulated apoptosis, compared to controls. In summary, the potential interactions between the ghrelin receptor isoforms, GHS-R1a and GHS-R1b, and the related zinc receptor, GPR39, and the potential for functional outcomes in prostate cancer were investigated using a number of independent methods. We did not definitively demonstrate the formation of these dimers using a number of state of the art methods to directly demonstrate receptor-receptor interactions. We investigated a number of potential functions of GPR39 and GHS-R1a in the prostate and did not observe altered function in response to co-expression of these receptors. The technical questions raised by this study highlight the requirement for the application of extensive controls when using current methods for the demonstration of GPCR dimerisation. Similar findings in this field reflect the current controversy surrounding the investigation of GPCR dimerisation. Although GHS-R1a/GHS-R1b or GHS-R1a/GPR39 heterodimerisation was not clearly demonstrated, this study provides a basis for future investigations of these receptors in prostate cancer. Additionally, the results presented in this study and growing evidence in the literature highlight the requirement for an extensive understanding of the experimental method and the performance of a range of controls to avoid the spurious interpretation of data gained from artificial expression systems. The future development of more robust techniques for investigating GPCR dimerisation is clearly required and will enable us to elucidate whether GHS-R1a, GHS-R1b and GPR39 form physiologically relevant dimers.