Improved earthwork allocation planning for fuel consumption and emissions reduction in linear infrastructure construction – case study data

This document provides data for the case study presented in our recent earthwork planning papers. Some results are also provided in a graphical format using Excel.

Spatiotemporal modelling in estimation of nitrous oxide emissions from soil

Nitrous oxide is a major greenhouse gas emission. The aim of this research was to develop and apply statistical models to characterize the complex spatial and temporal variation in nitrous oxide emissions from soils under different land use conditions. This is critical when developing site-specific management plans to reduce nitrous oxide emissions. These studies can improve predictions and increase our understanding of environmental factors that influence nitrous oxide emissions. They also help to identify areas for future research, which can further improve the prediction of nitrous oxide in practice.

Effect of pulsed power on particle matter in diesel engine exhaust using a DBD plasma reactor

Nonthermal plasma (NTP) treatment of exhaust gas is a promising technology for both nitrogen oxides (NOX) and particulate matter (PM) reduction by introducing plasma into the exhaust gases. This paper considers the effect of NTP on PM mass reduction, PM size distribution, and PM removal efficiency. The experiments are performed on real exhaust gases from a diesel engine. The NTP is generated by applying high-voltage pulses using a pulsed power supply across a dielectric barrier discharge (DBD) reactor. The effects of the applied high-voltage pulses up to 19.44 kVpp with repetition rate of 10 kHz are investigated. In this paper, it is shown that the PM removal and PM size distribution need to be considered both together, as it is possible to achieve high PM removal efficiency with undesirable increase in the number of small particles. Regarding these two important factors, in this paper, 17 kVpp voltage level is determined to be an optimum point for the given configuration. Moreover, particles deposition on the surface of the DBD reactor is found to be a significant phenomenon, which should be considered in all plasma PM removal tests.

Aircraft collision avoidance using spherical visual predictive control and single point features

This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

Driver perceptions of the benefits of reducing their driving speed on safety, emissions, and stress and road rage

The existing literature shows driving speed significantly affects levels of safety, emissions, and stress in driving. In addition, drivers who feel tense when driving have been found to drive more slowly than others. These findings were mostly obtained from crash data analyses or field studies, and less is known regarding driver perceptions of the extent to which reducing their driving speed would improve road safety, reduce their car’s emissions, and reduce stress and road rage. This paper uses ordered probit regression models to analyse responses from 3538 Queensland drivers who completed an online RACQ survey. Drivers most strongly agreed that reducing their driving speed would improve road safety, less strongly agreed that reducing their driving speed would reduce their car’s emissions and least strongly agreed that reducing their driving speed would reduce stress and road rage. Younger drivers less strongly agreed that these benefits would occur than older drivers. Drivers of automatic cars and those who are bicycle commuters agreed more to these benefits than other drivers. Female drivers agreed more strongly than males on improving safety and reducing stress and road rage. Type of fuel used, engine size, driving experience, and distance driven per week were also found to be associated with driver perceptions, although these were not found to be significant in all of the regression models. The findings from this study may help in developing targeted training or educational measures to improve drivers’ willingness to reduce their driving speed.

A flexible Bayesian model for describing temporal variability of N2O emissions from an Australian pasture

Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

The microbial content of vacuum cleaner bag dust and emitted bioaerosols : implications for human exposures indoors

Vacuum cleaners can release large concentrations of particles, both in their exhaust air and from resuspension of settled dust. However, the size, variability and microbial diversity of these emissions are unknown, despite evidence to suggest they may contribute to allergic responses and infection transmission indoors. This study aimed to evaluate bioaerosol emission from various vacuum cleaners. We sampled the air in an experimental flow tunnel where vacuum cleaners were run and their airborne emissions sampled with closed-face cassettes. Dust samples were also 35 collected from the dust bag. Total bacteria, total archaea, Penicillium/Aspergillus and total Clostridium cluster 1 were quantified with specific qPCR protocols and emission rates were calculated. Clostridium botulinum, as well as antibiotic resistance genes were detected in each sample using endpoint PCR. Bacterial diversity was also analyzed using denaturing gel electrophoresis (DGGE), image analysis and band sequencing. We demonstrated that emission of bacteria and moulds (Pen/Asp) can reach values as high as 1E05/min and that those emissions are not related to each other. The bag dust bacterial and mould content was also consistently across the vacuums we assessed, reaching up to 1E07 bacteria or moulds equivalent/g. Antibiotic resistance genes were detected in several samples. No archaea or C. botulinum were detected in any air samples. Diversity analyses showed that most bacteria are from human sources, in keeping with other recent results. These results highlight the potential capability of vacuum cleaners to disseminate appreciable quantities of moulds and human-associated bacteria indoors and their role as a source of exposure to bioaerosols.

Influence of nitrogen fertiliser application and timing on greenhouse gas emissions from a lychee (Litchi chinensis) orchard in humid subtropical Australia

Nitrous oxide emissions from intensive, fertilised agricultural systems have been identified as significant contributors to both Australia's and the global greenhouse gas (GHG) budget. This is expected to increase as rates of agriculture intensification and land use change accelerate to support population growth and food production. Limited data exists on N2O trace gas fluxes from subtropical or tropical tree cropping soils critical for the development of effective mitigation strategies.This study aimed to quantify GHG emissions over two consecutive years (March 2007 to March 2009) from a 30 year (lychee) orchard in the humid subtropical region of Australia. GHG fluxes were measured using a combination of high temporal resolution automated sampling and manually sampled chambers. No fertiliser was added to the plots during the 2007 measurement season. A split application of nitrogen fertiliser (urea) was added at the rate of 265kgNha-1 during the autumn and spring of 2008. Emissions of N2O were influenced by rainfall events and seasonal temperatures during 2007 and the fertilisation events in 2008. Annual N2O emissions from the lychee canopy increased from 1.7kgN2O-Nha-1yr-1 for 2007, to 7.6kgN2O-Nha-1yr-1 following fertiliser application in 2008. This represented an emission factor of 1.56%, corrected for background emissions. The timing of the split application was found to be critical to N2O emissions, with over twice as much lost following an application in spring (2.44%) compared to autumn (EF: 1.10%). This research suggests that avoiding fertiliser application during the hot and moist spring/summer period can reduce N2O losses without compromising yields.

Control of infrastructure inspection aircraft vertical dynamics in the presence of thermal disturbances

The low-altitude aircraft inspection of powerlines, or other linear infrastructure networks, is emerging as an important application requiring specialised control technologies. Despite some recent advances in automated control related to this application, control of the underactuated aircraft vertical dynamics has not been completely achieved, especially in the presence of thermal disturbances. Rejection of thermal disturbances represents a key challenge to the control of inspection aircraft due to the underactuated nature of the dynamics and specified speed, altitude, and pitch constraints. This paper proposes a new vertical controller consisting of a backstepping elevator controller with feedforward-feedback throttle controller. The performance of our proposed approach is evaluated against two existing candidate controllers.

Fuel consumption and gas emissions of an automatic transmission vehicle following simple eco-driving instructions on urban roads

Following eco-driving instructions can reduce fuel consumption between 5 to 20% on urban roads with manual cars. The majority of Australian cars have an automatic transmission gear-box. It is therefore of interest to verify whether current eco-driving instructions are e cient for such vehicles. In this pilot study, participants (N=13) drove an instrumented vehicle (Toyota Camry 2007) with an automatic transmission. Fuel consumption of the participants was compared before and after they received simple eco-driving instructions. Participants drove the same vehicle on the same urban route under similar tra c conditions. We found that participants drove at similar speeds during their baseline and eco-friendly drives, and reduced the level of their accelerations and decelerations during eco-driving. Fuel consumption decreased for the complete drive by 7%, but not on the motorway and inclined sections of the study. Gas emissions were estimated with the VT-micro model, and emissions of the studied pollutants (CO2, CO, NOX and HC) were reduced, but no di erence was observed for CO2 on the motorway and inclined sections. The di erence for the complete lap is 3% for CO2. We have found evidence showing that simple eco-driving instructions are e cient in the case of automatic transmission in an urban environment, but towards the lowest values of the spectrum of fuel consumption reduction from the di erent eco-driving studies.

Precedent-free fault isolation in a diesel engine exhaust gas recirculation system

In this paper, a recently introduced model-based method for precedent-free fault detection and isolation (FDI) is modified to deal with multiple input, multiple output (MIMO) systems and is applied to an automotive engine with exhaust gas recirculation (EGR) system. Using normal behavior data generated by a high fidelity engine simulation, the growing structure multiple model system (GSMMS) approach is used to construct dynamic models of normal behavior for the EGR system and its constituent subsystems. Using the GSMMS models as a foundation, anomalous behavior is detected whenever statistically significant departures of the most recent modeling residuals away from the modeling residuals displayed during normal behavior are observed. By reconnecting the anomaly detectors (ADs) to the constituent subsystems, EGR valve, cooler, and valve controller faults are isolated without the need for prior training using data corresponding to particular faulty system behaviors.

Sulfur resistant emissions catalyst

A catalyst comprising one or more complex oxides having a nominal compn. as set out in formula (1): AxB1-y-zMyPzOn (1) wherein A is selected from one or more group III elements including the lanthanide elements or one or more divalent or monovalent cations; B is selected from one or more elements with at. no. 22 to 24, 40 to 42 and 72 to 75; M is selected from one or more elements with at. no. 25 to 30; P is selected from one or more elements with at. no. 44 to 50 and 76 to 83; x is defined as a no. where 0

Continuous remote emissions monitoring – the lynchpin for air quality management

Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.

Enabling aircraft emergency landings using active visual site detection

The ability to automate forced landings in an emergency such as engine failure is an essential ability to improve the safety of Unmanned Aerial Vehicles operating in General Aviation airspace. By using active vision to detect safe landing zones below the aircraft, the reliability and safety of such systems is vastly improved by gathering up-to-the-minute information about the ground environment. This paper presents the Site Detection System, a methodology utilising a downward facing camera to analyse the ground environment in both 2D and 3D, detect safe landing sites and characterise them according to size, shape, slope and nearby obstacles. A methodology is presented showing the fusion of landing site detection from 2D imagery with a coarse Digital Elevation Map and dense 3D reconstructions using INS-aided Structure-from-Motion to improve accuracy. Results are presented from an experimental flight showing the precision/recall of landing sites in comparison to a hand-classified ground truth, and improved performance with the integration of 3D analysis from visual Structure-from-Motion.

HMM relative entropy rate concepts for vision-based aircraft manoeuvre detection

Machine vision is emerging as a viable sensing approach for mid-air collision avoidance (particularly for small to medium aircraft such as unmanned aerial vehicles). In this paper, using relative entropy rate concepts, we propose and investigate a new change detection approach that uses hidden Markov model filters to sequentially detect aircraft manoeuvres from morphologically processed image sequences. Experiments using simulated and airborne image sequences illustrate the performance of our proposed algorithm in comparison to other sequential change detection approaches applied to this application.