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  • (2022) Zhang, Qi
    Thesis
    As a dominant terrestrial ecosystem of the Earth, forest environments play profound roles in ecology, biodiversity, resource utilization, and management, which highlights the significance of forest characterization and monitoring. Some forest parameters can help track climate change and quantify the global carbon cycle and therefore attract growing attention from various research communities. Compared with traditional in-situ methods with expensive and time-consuming field works involved, airborne and spaceborne remote sensors collect cost-efficient and consistent observations at global or regional scales and have been proven to be an effective way for forest monitoring. With the looming paradigm shift toward data-intensive science and the development of remote sensors, remote sensing data with higher resolution and diversity have been the mainstream in data analysis and processing. However, significant heterogeneities in the multi-source remote sensing data largely restrain its forest applications urging the research community to come up with effective synergistic strategies. The work presented in this thesis contributes to the field by exploring the potential of the Synthetic Aperture Radar (SAR), SAR Polarimetry (PolSAR), SAR Interferometry (InSAR), Polarimetric SAR Interferometry (PolInSAR), Light Detection and Ranging (LiDAR), and multispectral remote sensing in forest characterization and monitoring from three main aspects including forest height estimation, active fire detection, and burned area mapping. First, the forest height inversion is demonstrated using airborne L-band dual-baseline repeat-pass PolInSAR data based on modified versions of the Random Motion over Ground (RMoG) model, where the scattering attenuation and wind-derived random motion are described in conditions of homogeneous and heterogeneous volume layer, respectively. A boreal and a tropical forest test site are involved in the experiment to explore the flexibility of different models over different forest types and based on that, a leveraging strategy is proposed to boost the accuracy of forest height estimation. The accuracy of the model-based forest height inversion is limited by the discrepancy between the theoretical models and actual scenarios and exhibits a strong dependency on the system and scenario parameters. Hence, high vertical accuracy LiDAR samples are employed to assist the PolInSAR-based forest height estimation. This multi-source forest height estimation is reformulated as a pan-sharpening task aiming to generate forest heights with high spatial resolution and vertical accuracy based on the synergy of the sparse LiDAR-derived heights and the information embedded in the PolInSAR data. This process is realized by a specifically designed generative adversarial network (GAN) allowing high accuracy forest height estimation less limited by theoretical models and system parameters. Related experiments are carried out over a boreal and a tropical forest to validate the flexibility of the method. An automated active fire detection framework is proposed for the medium resolution multispectral remote sensing data. The basic part of this framework is a deep-learning-based semantic segmentation model specifically designed for active fire detection. A dataset is constructed with open-access Sentinel-2 imagery for the training and testing of the deep-learning model. The developed framework allows an automated Sentinel-2 data download, processing, and generation of the active fire detection results through time and location information provided by the user. Related performance is evaluated in terms of detection accuracy and processing efficiency. The last part of this thesis explored whether the coarse burned area products can be further improved through the synergy of multispectral, SAR, and InSAR features with higher spatial resolutions. A Siamese Self-Attention (SSA) classification is proposed for the multi-sensor burned area mapping and a multi-source dataset is constructed at the object level for the training and testing. Results are analyzed by different test sites, feature sources, and classification methods to assess the improvements achieved by the proposed method. All developed methods are validated with extensive processing of multi-source data acquired by Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), Land, Vegetation, and Ice Sensor (LVIS), PolSARproSim+, Sentinel-1, and Sentinel-2. I hope these studies constitute a substantial contribution to the forest applications of multi-source remote sensing.

  • (2022) Zhao, Runqing
    Thesis
    Emerging modes of air transport such as autonomous airport shuttle and air taxi are potentially efficient alternatives to current transport practices such as bus and train. This thesis examines bus shuttle service within an airport and air metro as two examples of network design. Within an airport, the bus shuttle serves passengers between the terminals, train stations, parking lots, hotels, and shopping areas. Air metro is a type of pre-planned service in urban air mobility that accommodates passengers for intra- or inter-city trips. The problems are to optimise the service, and the outputs including the optimal fleet size, dispatch pattern and schedule. Based on the proposed time-space networks, the service network design problems are formulated as mixed integer linear programs. The heterogeneous multi-type bus fleet case and stochastic demand case are extended for the airport shuttle case, while a rolling horizon optimisation is adopted for the air metro case. In the autonomous airport inter-terminal bus shuttle case, a Monte Carlo simulation-based approach is proposed to solve the case with demand stochasticity, which is then further embedded into an "effective" passenger demand framework. The "effective" demand is the summation of mean demand value and a safety margin. By comparing the proposed airport shuttle service to the current one, it is found that the proposed service can save approximately 27% of the total system cost. The results for stochastic problem suggest estimating the safety margin to be 0.3675 times of the standard deviation brings the best performance. For the second case, the service network design is extended with a pilot scheduling layer and simulation is undertaken to compare the autonomous (pilot-less) and piloted service design. The results suggest that an autonomous air metro service would be preferable if the price of an autonomous aircraft is less than 1.6 times the price of a human-driven one. The results for rolling horizon optimisation suggest to confirm the actual demand at least 45 minutes prior to departure. Based on data from the Sydney (Australia) region, the thesis provides information directly relevant for the service network design of emerging modes of air transport in the city.

  • (2022) Cao, Jun
    Thesis
    This thesis focuses on the development and applications of magnetic resonance electrical properties tomography (MREPT), which is an emerging imaging modality to noninvasively obtain the electrical properties of tissues, such as conductivity and permittivity. Chapter 2 describes the general information about human research ethics, MRI scanner, MR sequence and the method of phase-based MREPT implemented in this thesis. Chapter 3 examines the repeatability of phase-based MREPT in the brain conductivity measurement using balanced fast field echo (bFFE) and turbo spin echo (TSE) sequences, and investigate the effects of compressed SENSE, whole-head B_1 shimming and video watching during scan on the measurement precision. Chapter 4 investigates the conductivity signal in response to short-duration visual stimulus, compares the signal and functional activation pathway with that of BOLD, and tests the consistency of functional conductivity imaging (funCI) with visual stimulation across participants. Chapter 5 extends the use of functional conductivity imaging to somatosensory stimulation and trigeminal nerve stimulation to evaluate the consistency of functional conductivity activation across different types of stimuli. In addition, visual adaptation experiment is performed to test if the repetition suppression effect can be observed using funCI. Chapter 6 explores if resting state conductivity networks can be reliably constructed using resting state funCI, evaluates the consistency of persistent homology architectures, and compares the links between nodes in the whole brain. Chapter 7 investigates the feasibility of prostate conductivity imaging using MREPT, and distinctive features in the conductivity distribution between healthy participants and participants with suspected abnormalities.

  • (2022) Shahriari, Siroos
    Thesis
    Time series models are used to model, simulate, and forecast the behaviour of a phenomenon over time based on data recorded over consistent intervals. The digital era has resulted in data being captured and archived in unprecedented amounts, such that vast amounts of information are available for analysis. Feature-rich time-series datasets are one of the data sets that have become available due to the expanding trend of data collection technologies worldwide. With the application of time series analysis to support financial and managerial decision-making, the development and advancement of time series models in the transportation domain are unavoidable. As a result, this thesis redefines time series models for transportation planning use with the following three aims: (1) To combine parametric and bootstrapping techniques within time series models; (2) to develop a time series model capable of modelling both temporal and spatial dependencies in time-series data; and (3) to leverage the hierarchical Bayesian modelling paradigm to accommodate flexible representations of heterogeneity in data. The first main chapter introduces an ensemble of ARIMA models. It compares its performance against conventional ARIMA (a parametric method) and LSTM models (a non-parametric method) for short-term traffic volume prediction. The second main chapter introduces a copula time series model that describes correlations between variables through time and space. Temporal correlations are modelled by an ARMA-GARCH model which enables a modeller to describe heteroscedastic data. The copula model has a flexible correlation structure and is used to model spatial correlations with the ability to model nonlinear, tailed and asymmetric correlations. The third main chapter provides a Bayesian modelling framework to raise awareness about using hierarchical Bayesian approaches for transport time series data. In addition, this chapter presents a Bayesian copula model. The combination of the two models provides a fully Bayesian approach to modelling both temporal and spatial correlations. Compared with frequentist models, the proposed modelling structures can incorporate prior knowledge. In the fourth main chapter, the fully Bayesian model is used to investigate mobility patterns before, during and after the COVID-19 pandemic using social media data. A more focused analysis is conducted on the mobility patterns of Twitter users from different zones and land use types.

  • (2022) Wang, Shuangyue
    Thesis
    Two-dimensional transition metal dichalcogenide (TMD) nanocrystals (NCs) exhibit unique optical and electrocatalytic properties. However, the growth of uniform and high-quality NCs of monolayer TMD remains a challenge. Until now, most of them are synthesized via solution-based hydrothermal process or ultrasonic exfoliation method, in which the capping ligands introduced from organic solution often quench the optical and electrocatalytic properties of TMD NCs. Moreover, it is difficult to homogeneously disperse the solution-based TMD NCs on a substrate for device fabrication since the dispersed NCs can easily aggregate. Here, we put forward a novel CVD method to grow closely-spaced TMD NCs and explored the growth mechanism and attempts on the size control. Their applications acting as electrocatalysts and adhesion layer for Au film deposition have been also well displayed. Through the whole chapters of this thesis, the following aspects are highlighted: 1. MoS2 and other TMD nanocrystals have been grown on the c-plane sapphire. The surface oxygen vacancies determine the density of TMD nanocrystals. The MoS2 nanocrystals demonstrate excellent hydrogen evolution reaction and surface-enhanced Raman scattering performance owing to the abundant edges. 2. Deep insights into the growth of MoS2 nanograins have been explored. The surface step edges and lattice structures of the underlying sapphire substrates have a significant influence on the growth behaviors. The step edges could modulate the aggregation of MoS2 nanograins to form unidirectional triangular islands. The Raman spectra of MoS2 demonstrate a linear relationship with the crystal size of MoS2. 3. The orientation of sapphire substrate has an of importance effect on the critical size of MoS2 nanocrystals. The MoS2 nanocrystals have the smallest size on the r-plane sapphire, besides, the MoS2 on r-plane sapphire demonstrates the sintering-resistance feature, which is attributed to the edge-pinning effect when MoS2 edges are anchored on the sapphire surface. 4. The MoS2 nanocrystalline layer was utilized as the adhesion layer for Au film depositing on a sapphire substrate. The Au films on MoS2 displayed superior transmittance and electrical conductivity as well as outstanding thermal stability, which lay in the strong binding of Au film with MoS2 nanocrystalline layer.

  • (2022) Kaur, Sandeep
    Thesis
    Advances in molecular biology data collection, leading to the accumulation of large amounts of diverse data, call for novel computational approaches to enable their effective analysis. This thesis explored the application of visual-analytics-driven bioinformatics approaches to four biomolecular data-driven challenges. For analysing time-series omic and multiomic data, a novel method, Minardo-Model, was developed. Minardo-Model can identify key events (e.g. phosphorylation) from such time-series data and temporally order them. To visualise the inferred order of events, two novel visualisation approaches, event maps and event sparklines, were developed. Minardo-Model was tested using two time-series datasets and in both cases, the event orderings derived by this method correlated with prior knowledge. To streamline the use of experimental 3D protein structures for analysing sequence variants, a novel method was developed and integrated into Aquaria. For variants specified in the HGVS notation, the method identifies and displays a best matching structure. Additionally, for each variant specified, all structures spanning the variant, and containing the exact variant (missense only), along with sequence features retrieved from external resources, are summarised. The developed approach was used to analyse variants in human ACE2, and SARS-CoV-2 spike, revealing novel insights. For pathogenic bacterial isolates characterised using multilevel genome typing (MGT), the MGTdb web service was developed. MGTdb, enables upload of isolates as sequence reads or extracted alleles, which are processed and assigned the MGT-identifiers. The features of MGTdb, such as interactive visualisation tools, data download and export to external software, enable epidemiological exploration in the context of the local or global database of isolates. The usability of MGTdb was successfully demonstrated through three case studies. For identifying insertion sequences (IS) from short-read sequencing data, a novel method, WiIS, was developed. WiIS was tested on Bordetella pertussis isolates, for which both short-read (test data) and long-read sequences (ground truth) were available - WiIS was found to have high precision and recall. It also outperformed other published tools in identifying IS in B. pertussis genomes. The novel bioinformatics methods developed in this thesis enable novel analysis of a wide variety of data thus providing insight into various biomolecular processes.

  • (2022) Nguyen, Minh Triet
    Thesis
    Singlet fission is a photo-physical process that generates two triplet excitons from one singlet exciton and can potentially enhance efficiency in photovoltaic systems. The combination of photovoltaics and singlet fission is a novel field for solar energy conversion when there is much interest in renewable, non-destructive, and continuously available energy sources. Singlet fission can also overcome thermalization losses in photovoltaics, which happens in traditional cells when the incident photon energy is higher than the silicon bandgap energy, using a carrier multiplication mechanism. This thesis will design, construct, and characterize photovoltaic devices incorporating singlet fission materials to study singlet fission in practical application. The research focuses on materials characterization, spin dynamics, and electron transfers between acene and the semiconductor layer in Au/TiO2 ballistic cells, and the incorporation of singlet fission layers on silicon-based cell structures. In detail, a set of investigations was developed and summarized by implementing singlet fission materials into a state-of-the-art ballistic photovoltaic device and silicon-based solar cell. The studies demonstrate proof of concept and rationally explain the process. The first part of the thesis investigates thin films of pentacene, TIPS-pentacene, and tetracene via crystallinity, morphology, absorption, and thickness characterization. Additionally, Au and TiO2 layers in Schottky device structures were optimized to achieve the best performance for energy transfer from an applied dye layer (merbromin). The drop-casted dye layer influences the device performance by increasing short-circuit current and open-circuit voltage, demonstrating the ability of charge transfer between the device and the applied film. This device structure provides a test bed for studying charge and energy transfer from singlet fission films. The latter part of the thesis describes several investigations to understand singlet fission in a thin film using this architecture. Magneto-photoconductivity measurements were primarily used to observe the spin dynamics via photoconductivity under an external magnetic field. Control experiments with bare Au/TiO2 devices showed no observable magneto-photoconductivity signal. In contrast, devices with pentacene and tetracene singlet fission layers showed a strong magnetoconductivity effect caused by ballistic electron transfer from the singlet fission layer into the TiO2 n-type semiconductor through an ultra-thin gold layer inserted between the layers. A qualitatively different behavior is seen between the pentacene and tetracene, which reveals that the energy alignment plays a crucial part in the charge transfer between the singlet fission layer and the device. The last section investigates the application of pentacene and tetracene evaporated thin-films as sensitizer layers to a silicon-based solar cell. The optimized Si cell structure with the annealing treatment improved the cell's performance by increasing short-circuit current and open-circuit voltage. The deposition of pentacene and tetracene as sensitizer layers into the device showed some results but posed several challenges that need to be addressed. As the current-voltage and external quantum efficiency measurements were taken, it was observed that material interfaces need to be designed to fully achieve the singlet fission of the acene layer into the Si devices.

  • (2022) Qiao, Laicong
    Thesis
    There has been a rapid-growing market and academic enthusiasm for small wearable molecular diagnostic platforms driven by the growing demand for continuous monitoring of human health. Wearable devices need to be portable, stretchable, and ideally re-configurable to be able to work for different analytes. Such flexible physiological monitoring devices which are non-invasive or minimally-invasive represent the next frontier of biomedical diagnostics. They may make it possible to predict and prevent diseases or facilitate treatment by diagnosing diseases at the initial stages. However, there are many problems that restrict further applications of these devices. Firstly, there are a limited number of bio-materials which are highly flexible, biocompatible and have anti-fouling properties; such biomaterials are needed as substrates for wearable devices. Secondly, traditional biosensors used in wearable devices focus on the detection of physical signals (such as heartbeat) and small chemical molecules, e.g. Na+, K+. These are not sufficient to provide in depth health information which requires sensing of large molecules such as proteins, ideally in real time, which is currently challenging. This provides a motivation to develop highly sensitive wearable biosensors for the detection of large molecules in sweat. This thesis centres on the development of a bio-material based wearable device for continuous detection of crucial analytes in human sweat. To achieve this target, our first aim was to design a highly bio-compatible flexible material as a substrate for wearable devices. A tough and anti-fouling three-network hydrogel has been prepared by integrating a zwitterionic polymer network into a robust double-network hydrogel. Secondly, to fill the gap between technological development of continuous and non-invasive detection of different analytes in human sweat, a patterned sweat-based biosensor was created for the detection of key biomolecules. This sensor was produced by placing specific aptamers or enzymes on flexible working electrodes. In addition, nanotechnology methods have been applied to refine the bio-sensing interface to further increase the sensitivity of our sensors. Finally, a sample collection chip has been combined with our high sensitivity sensors to fabricate a wearable device for sweat bio-sensing purposes. Future research may involve integration of a commercially available wireless signal readout module with this wearable biosensing device. The outcomes of this work may provide new insights for the development of wearable devices for continuous measurement of a spectrum of analytes in sweat, as an important step towards point-of-care diagnostics

  • (2022) Melodia, Daniele
    Thesis
    Antibodies are increasingly useful therapeutics, and examples include the checkpoint inhibitors pembrolizumab1 and ipilimumab2 in cancer immunotherapy, and anti tau therapies in Alzheimer’s disease and dementia.3,4 However, specific applications requiring cytosolic delivery of the antibody, or transport across the blood-brain barrier pose challenges to antibody therapeutics. These issues may reduce the effectiveness of immunotherapy and restrict it to extracellular targets. Conjugating polymers to proteins and enzymes has been very effective at improving their stability and pharmacokinetics,5–8 and similar approaches have been studied for antibody conjugation.9–12 Finding an effective polymeric delivery system for antibodies can greatly improve immunotherapy. In this work three strategies were explored for the encapsulation and bioconjugation to antibodies. The first approach is the encapsulation via electrostatic interactions between the antibody and a charged block copolymer to form polyion complex (PIC) micelles. Polyphosphonium block copolymers were studied for the first time to encapsulate antibodies, and were compared to their ammonium counterpart. While this approach has the advantage of being reversible, the polymer-antibody electrostatic interactions were too weak for biological applications, and delivery by this means would require a crosslinking strategy. The second approach involves covalent attachment of polymers on the antibody’s surface via a grafting from polymerisation. An oxygen tolerant technique was employed for the screening of a large number of samples in low volumes (<100 μL). Successful grafting was demonstrated by AF4 and gel electrophoresis. Enzyme-linked immunosorbent assay (ELISA) showed retention of up to 40% binding activity relative to the native antibody with a marked improvement in stability. The third strategy introduces a novel acid sensitive linker for the reversible covalent attachment of polymers to the antibody’s surface. This was achieved by using Diels-Alder chemistry to create an activated PEG that forms an amide with a conformational lock similar to citraconic anhydride upon conjugation to the amines on the antibody. The ability of the linker to cleave at pH 5.5 is demonstrated, resulting in almost complete recovery of the original binding activity of the antibody. Overall, the reversible covalent attachment investigated here seems the most promising, and combining the high throughput method with the cleavable linker approach holds great potential for advancing in immunotherapy. References (1) Reck, M. Pembrolizumab as First-Line Therapy for Metastatic Non-Small-Cell Lung Cancer. Futur. Med. 2018, 10, 93–105. (2) Gao, J.; Ward, J. F.; Pettaway, C. A.; Shi, L. Z.; Subudhi, S. K.; Vence, L. M.; Zhao, H.; Chen, J.; Chen, H.; Efstathiou, E.; Troncoso, P.; Allison, J. P.; Logothetis, C. J.; Wistuba, I. I.; Sepulveda, M. A.; Sun, J.; Wargo, J.; Blando, J. VISTA Is an Inhibitory Immune Checkpoint That Is Increased after Ipilimumab Therapy in Patients with Prostate Cancer. Nat. Med. 2017, 23 (5), 551–555.. (3) Pedersen, J. T.; Sigurdsson, E. M. Tau Immunotherapy for Alzheimer’s Disease. Trends Mol. Med. 2015, 21 (6), 394–402. (4) Castillo-Carranza, D. L.; Sengupta, U.; Guerrero-Munoz, M. J.; Lasagna-Reeves, C. A.; Gerson, J. E.; Singh, G.; Estes, D. M.; Barrett, A. D. T.; Dineley, K. T.; Jackson, G. R.; Kayed, R. Passive Immunization with Tau Oligomer Monoclonal Antibody Reverses Tauopathy Phenotypes without Affecting Hyperphosphorylated Neurofibrillary Tangles. J. Neurosci. 2014, 34 (12), 4260–4272. (5) Abolmaali, S. S.; Tamaddon, A. M.; Salmanpour, M.; Mohammadi, S.; Dinarvand, R. Block Ionomer Micellar Nanoparticles from Double Hydrophilic Copolymers, Classifications and Promises for Delivery of Cancer Chemotherapeutics. Eur. J. Pharm. Sci. 2017, 104 (January), 393–405. (6) Kurakhmaeva, K. B.; Djindjikhashvili, I. A.; Petrov, V. E.; Balabanyan, V. U.; Voronina, T. A.; Trofimov, S. S.; Kreuter, J.; Gelperina, S.; Begley, D.; Alyautdin, R. N. Brain Targeting of Nerve Growth Factor Using Poly(Butyl Cyanoacrylate) Nanoparticles. J. Drug Target. 2009, 17 (8), 564–574. (7) Jiang, Y.; Fay, J. M.; Poon, C. D.; Vinod, N.; Zhao, Y.; Bullock, K.; Qin, S.; Manickam, D. S.; Yi, X.; Banks, W. A.; Kabanov, A. V. Nanoformulation of Brain-Derived Neurotrophic Factor with Target Receptor-Triggered-Release in the Central Nervous System. Adv. Funct. Mater. 2017, 1703982, 1–11. (8) Klyachko, N. L.; Manickam, D. S.; Brynskikh, A. M.; Uglanova, S. V.; Li, S.; Higginbotham, S. M.; Bronich, T. K.; Batrakova, E. V.; Kabanov, A. V. Cross-Linked Antioxidant Nanozymes for Improved Delivery to CNS. Nanomedicine Nanotechnology, Biol. Med. 2012, 8 (1), 119–129. (9) Bin Liu, Khushboo Singh , Shuai Gong , Mine Canakci, Barbara A. Osborne, and S. T. Protein Antibody Conjugates PACs A Plug‐and‐Play Strategy for Covalent Conjugation and Targeted Intracellular Delivery of Pristine Proteins. Angew. Chemie 2021, 133, 12923–12928. (10) Chan, L. J.; Bulitta, J. B.; Ascher, D. B.; Haynes, J. M.; Mcleod, V. M.; Porter, C. J. H.; Williams, C. C.; Kaminskas, L. M. PEGylation Does Not Signi Fi Cantly Change the Initial Intravenous or Subcutaneous Pharmacokinetics or Lymphatic Exposure of Trastuzumab in Rats but Increases Plasma Clearance after Subcutaneous Administration. Mol. Pharm. 2015, 12, 794–809. (11) Subasic, C. N.; Ardana, A.; Chan, L. J.; Huang, F.; Scoble, J. A.; Butcher, N. J.; Meagher, L.; Chiefari, J.; Kaminskas, L. M.; Williams, C. Poly ( HPMA- Co -NIPAM ) Copolymer as an Alternative to Polyethylene Glycol-Based Pharmacokinetic Modulation of Therapeutic Proteins. Int. J. Pharm. 2021, 608 (September), 121075. (12) Keita Hironaka,a,b Erika Yoshihara, Ahmed Nabil, James J. Lai, A. K. and M. E. Conjugation of Antibody with Temperature-Responsive Polymer via in Situ Click Reaction to Enable Biomarker Enrichment for Increased Diagnostic Sensitivity. Biomater. Sci. 2021, 9, 4870–4879.

  • (2022) Oudone, Phetdala
    Thesis
    Dissolved organic carbon is stored and processed in groundwater in three ways. It is stored on minerals by adsorption, it is biologically processed through biodegradation, and it also undergoes a process to return to groundwater called desorption. This biophysiochemical research shows that the groundwater system is therefore a vital part of the global carbon cycle and carbon sink. This research fills a gap in the existing understanding of how to calculate the global carbon budget, as does not yet include the dissolved organic carbon that is stored in groundwater. This thesis exclusively explores processes determining dissolved organic carbon character and concentration in groundwater in different geological environments. This is new, useful knowledge to describe the biophysiochemical process. This research did not examine human interference in adding carbon to groundwater. This research found how dissolved organic carbon is stored and processed in groundwater due to biodegradation and desorption, and how it is adsorbed onto sediment surface. This research explored the characteristics and concentration of Dissolved organic carbon in groundwater by using Liquid Chromatography-Organic Carbon Detection, and other techniques, to examine dissolved organic carbon in terms of its fractions: humic substances, hydrophobic organic carbon, biopolymers, building blocks (BB), low molecular weight neutrals and low molecular weight acids. There were several key findings. First, the results showed that both semi-arid inland low sedimentary organic carbon environments – i.e., Maules Creek and Wellington – were a carbon source; while the high rainfall temperate coastal peatland environment of Anna Bay was a carbon sink. Secondly, another key finding was that dissolved organic carbon was not processed as a whole chemical compound, but it was processed by its fractions where each fraction was processed distinctly. For example, humic substances were only adsorbed/desorbed in groundwater; while low molecular weight neutrals were only consumed by microbes in the biodegradation process in groundwater.