Offsetting greenhouse gas emissions through biological carbon sequestration in North Eastern Australia

The Kyoto Protocol recognises trees as a sink of carbon and a valid means to offset greenhouse gas emissions and meet internationally agreed emissions targets. This study details biological carbon sequestration rates for common plantation species Araucaria cunninghamii (hoop pine), Eucalyptus cloeziana, Eucalyptus argophloia, Pinus elliottii and Pinus caribaea var hondurensis and individual land areas required in north-eastern Australia to offset greenhouse gas emissions of 1000tCO 2e. The 3PG simulation model was used to predict above and below-ground estimates of biomass carbon for a range of soil productivity conditions for six representative locations in agricultural regions of north-eastern Australia. The total area required to offset 1000tCO 2e ranges from 1ha of E. cloeziana under high productivity conditions in coastal North Queensland to 45ha of hoop pine in low productivity conditions of inland Central Queensland. These areas must remain planted for a minimum of 30years to meet the offset of 1000tCO 2e.

Non-destructive evaluation of articular cartilage defects using near-infrared (NIR) spectroscopy in osteoarthritic rat models and its direct relation to Mankin Score

Objective The aim of this study was to demonstrate the potential of near-infrared (NIR) spectroscopy for categorizing cartilage degeneration induced in animal models. Method Three models of osteoarthritic degeneration were induced in laboratory rats via one of the following methods: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACLT); and (iii) intra-articular injection of mono-ido-acetete (1 mg) (MIA), in the right knee joint, with 12 rats per model group. After 8 weeks, the animals were sacrificed and tibial knee joints were collected. A custom-made nearinfrared (NIR) probe of diameter 5 mm was placed on the cartilage surface and spectral data were acquired from each specimen in the wavenumber range 4 000 – 12 500 cm−1. Following spectral data acquisition, the specimens were fixed and Safranin–O staining was performed to assess disease severity based on the Mankin scoring system. Using multivariate statistical analysis based on principal component analysis and partial least squares regression, the spectral data were then related to the Mankinscores of the samples tested. Results Mild to severe degenerative cartilage changes were observed in the subject animals. The ACLT models showed mild cartilage degeneration, MSX models moderate, and MIA severe cartilage degenerative changes both morphologically and histologically. Our result demonstrate that NIR spectroscopic information is capable of separating the cartilage samples into different groups relative to the severity of degeneration, with NIR correlating significantly with their Mankinscore (R2 = 88.85%). Conclusion We conclude that NIR is a viable tool for evaluating articularcartilage health and physical properties such as change in thickness with degeneration.

Physicochemical characterization of particulate emissions from a compression ignition engine employing two injection technologies and three fuels

Alternative fuels and injection technologies are a necessary component of particulate emission reduction strategies for compression ignition engines. Consequently, this study undertakes a physicochemical characterization of diesel particulate matter (DPM) for engines equipped with alternative injection technologies (direct injection and common rail) and alternative fuels (ultra low sulfur diesel, a 20% biodiesel blend, and a synthetic diesel). Particle physical properties were addressed by measuring particle number size distributions, and particle chemical properties were addressed by measuring polycyclic aromatic hydrocarbons (PAHs) and reactive oxygen species (ROS). Particle volatility was determined by passing the polydisperse size distribution through a thermodenuder set to 300 °C. The results from this study, conducted over a four point test cycle, showed that both fuel type and injection technology have an impact on particle emissions, but injection technology was the more important factor. Significant particle number emission (54%–84%) reductions were achieved at half load operation (1% increase–43% decrease at full load) with the common rail injection system; however, the particles had a significantly higher PAH fraction (by a factor of 2 to 4) and ROS concentrations (by a factor of 6 to 16) both expressed on a test-cycle averaged basis. The results of this study have significant implications for the health effects of DPM emissions from both direct injection and common rail engines utilizing various alternative fuels.

Concentration and oxidative potential of on-road particle emissions and their relationship with traffic composition : Relevance to exposure assessment

Particles emitted by vehicles are known to cause detrimental health effects, with their size and oxidative potential among the main factors responsible. Therefore, understanding the relationship between traffic composition and both the physical characteristics and oxidative potential of particles is critical. To contribute to the limited knowledge base in this area, we investigated this relationship in a 4.5 km road tunnel in Brisbane, Australia. On-road concentrations of ultrafine particles (<100 nm, UFPs), fine particles (PM2.5), CO, CO2 and particle associated reactive oxygen species (ROS) were measured using vehicle-based mobile sampling. UFPs were measured using a condensation particle counter and PM2.5 with a DustTrak aerosol photometer. A new profluorescent nitroxide probe, BPEAnit, was used to determine ROS levels. Comparative measurements were also performed on an above-ground road to assess the role of emission dilution on the parameters measured. The profile of UFP and PM2.5 concentration with distance through the tunnel was determined, and demonstrated relationships with both road gradient and tunnel ventilation. ROS levels in the tunnel were found to be high compared to an open road with similar traffic characteristics, which was attributed to the substantial difference in estimated emission dilution ratios on the two roadways. Principal component analysis (PCA) revealed that the levels of pollutants and ROS were generally better correlated with total traffic count, rather than the traffic composition (i.e. diesel and gasoline-powered vehicles). A possible reason for the lack of correlation with HDV, which has previously been shown to be strongly associated with UFPs especially, was the low absolute numbers encountered during the sampling. This may have made their contribution to in-tunnel pollution largely indistinguishable from the total vehicle volume. For ROS, the stronger association observed with HDV and gasoline vehicles when combined (total traffic count) compared to when considered individually may signal a role for the interaction of their emissions as a determinant of on-road ROS in this pilot study. If further validated, this should not be overlooked in studies of on- or near-road particle exposure and its potential health effects.

Near infrared spectroscopy for non-destructive evaluation of articular cartilage

There is a need for an accurate real-time quantitative system that would enhance decision-making in the treatment of osteoarthritis. To achieve this objective, significant research is required that will enable articular cartilage properties to be measured and categorized for health and functionality without the need for laboratory tests involving biopsies for pathological evaluation. Such a system would provide the capability of access to the internal condition of the cartilage matrix and thus extend the vision-based arthroscopy that is currently used beyond the subjective evaluation of surgeons. The system required must be able to non-destructively probe the entire thickness of the cartilage and its immediate subchondral bone layer. In this thesis, near infrared spectroscopy is investigated for the purpose mentioned above. The aim is to relate it to the structure and load bearing properties of the cartilage matrix to the near infrared absorption spectrum and establish functional relationships that will provide objective, quantitative and repeatable categorization of cartilage condition outside the area of visible degradation in a joint. Based on results from traditional mechanical testing, their innovative interpretation and relationship with spectroscopic data, new parameters were developed. These were then evaluated for their consistency in discriminating between healthy viable and degraded cartilage. The mechanical and physico-chemical properties were related to specific regions of the near infrared absorption spectrum that were identified as part of the research conducted for this thesis. The relationships between the tissue's near infrared spectral response and the new parameters were modeled using multivariate statistical techniques based on partial least squares regression (PLSR). With significantly high levels of statistical correlation, the modeled relationships were demonstrated to possess considerable potential in predicting the properties of unknown tissue samples in a quick and non-destructive manner. In order to adapt near infrared spectroscopy for clinical applications, a balance between probe diameter and the number of active transmit-receive optic fibres must be optimized. This was achieved in the course of this research, resulting in an optimal probe configuration that could be adapted for joint tissue evaluation. Furthermore, as a proof-of-concept, a protocol for obtaining the new parameters from the near infrared absorption spectra of cartilage was developed and implemented in a graphical user interface (GUI)-based software, and used to assess cartilage-on-bone samples in vitro. This conceptual implementation has been demonstrated, in part by the individual parametric relationship with the near infrared absorption spectrum, the capacity of the proposed system to facilitate real-time, non-destructive evaluation of cartilage matrix integrity. In summary, the potential of the optical near infrared spectroscopy for evaluating articular cartilage and bone laminate has been demonstrated in this thesis. The approach could have a spin-off for other soft tissues and organs of the body. It builds on the earlier work of the group at QUT, enhancing the near infrared component of the ongoing research on developing a tool for cartilage evaluation that goes beyond visual and subjective methods.

Hand-held monocular SLAM in thermal-infrared

Thermal-infrared imagery is relatively robust to many of the failure conditions of visual and laser-based SLAM systems, such as fog, dust and smoke. The ability to use thermal-infrared video for localization is therefore highly appealing for many applications. However, operating in thermal-infrared is beyond the capacity of existing SLAM implementations. This paper presents the first known monocular SLAM system designed and tested for hand-held use in the thermal-infrared modality. The implementation includes a flexible feature detection layer able to achieve robust feature tracking in high-noise, low-texture thermal images. A novel approach for structure initialization is also presented. The system is robust to irregular motion and capable of handling the unique mechanical shutter interruptions common to thermal-infrared cameras. The evaluation demonstrates promising performance of the algorithm in several environments.

Monitoring charged particle and ion emissions from a laser printer

While the emission rate of ultrafine particles has been measured and quantified, there is very little information on the emission rates of ions and charged particles from laser printers. This paper describes a methodology that can be adopted for measuring the surface charge density on printed paper and the ion and charged particle emissions during operation of a high-emitting laser printer and shows how emission rates of ultrafine particles, ions and charged particles may be quantified using a controlled experiment within a closed chamber.

CO2 emissions from the combustion of native Australian trees

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.