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Microalgae have tremendous potential for producing liquid renewable fuel. Many methods for converting microalgae to biofuel have been proposed; however, an economical and energetically feasible route for algal fuel production is yet to be found. This paper presents a review on the comparison of the most promising conversion pathways of microalgae to liquid fuel: hydrothermal liquefaction (HTL), wet extraction and non-destructive extraction. The comparison is based on important assessment parameters of product quality and yield, nutrient recovery, GHG emissions, energy and the cost associated with the production of fuel from microalgae, in order to better understand the pros and cons of each method. It was found that the HTL pathway produces more oil than the wet extraction pathway; however, higher concentrations of unwanted components are present in the HTL oil produced. Less nutrients (N and P) can be recovered in HTL compared to wet extraction. HTL consumes more fossil energy and generates higher GHG emissions than wet extraction, while the production cost of fuel from HTL pathway is lower than wet extraction pathway. There is considerable uncertainty in the comparison of the energy consumption and economics of the HTL pathway and the wet extraction pathway due to different scenarios analysed in the assessment studies. To be able to appropriately compare methodologies, the conversion methods should be analysed from growth to upgradation of oil utilising sufficiently similar assumptions and scenarios. Based on the data in available literature, wet oil extraction is the more appropriate system for biofuel production than HTL. However, the potential of alternative extraction/conversion technologies, such as, non-destructive extraction, need to be further assessed.

In recent years, sustainability concerns have gained increasing attention among countries and stakeholders worldwide. Towards the transition to sustainable rural development, the rural web framework (RWF) has become a consistent tool. Indicators from the RWF have been used to explore sustainable rural development for decision-making tasks, which improves the social, economic, and environmental performance of rural regions. However, the application of the RWF in studies is on the decline. Furthermore, there is a lack of literature reviews on the importance of the RWF and its relationship with different facets of sustainable development. We conducted a systematic literature review (SLR) (a) to explore how studies have used the RWF in the context of sustainable development and (b) to identify areas for further research. This study found that the RWF has mostly been used in developed countries, with fewer applications in developing countries. We suggest that there should be increased application of the RWF, particularly in developing countries, to broaden the rural web–sustainable development discourse and its relevance. This paper presents several areas where the indicators of the RWF can be applied to illustrate their relevance for policy decisions towards the achievement of the sustainable development goals (SDGs).

Abstract There are instances in remote areas where heat is being wasted, e.g., in internal combustion, engines, etc. Some of this heat can be recovered to produce distilled water in solar stills. The solar still replaces the cooling tower, ponds, or radiators normally used to control the engine temperature. The diesel cooling water in such a system remains separate from the saline water in the solar still. The advantages of using such a system compared with a conventional solar still are: 1. (a) water costs are very much reduced 2. (b) the area occupied is much less, i.e., about 1 5 th 3. (c) production has much less seasonal variation 4. (d) the efficiency of the solar still is improved due to the higher operating temperatures. From experiments conducted at Highett using a Mk VI solar still fitted with a simple heat exchanger and a separate electrically-heated source of hot water to simulate the waste heat, design data are not available for application to working systems. The information required to match a solar still to a diesel's cooling requirement is: 1. (a) engine efficiency 2. (b) hourly fuel consumption 3. (c) hourly solar radiation 4. (d) hourly ambient temperatures. A by-product of this work has been the production of a “solar water heater” which costs less than that of the cheapest conventional system. This “solar” hot water system uses a heat exchanger similar to what is used to transfer the waste heat to the saline water. It is envisaged to have hot water productions approximately the same as the distilled water productions. The influence of hot water production on the output of the waste heat solar still is discussed.

Abstract In Australia, the government spending on public buildings’ energy and water consumption is considerable; however the building energy and water retrofit market potential has been diminished by a number of barriers, especially financial. In contrast, in other advanced economies there are several reported financing strategies that have been shown to accelerate retrofit projects implementation. In this study, a coupled Bayesian Network – System Dynamics model was developed with the core aim to assess the likely influence of those novel financing options and procurement procedures on public building retrofit outcomes scenarios in the Australian context. A particular case-study focusing on Australian public hospitals was showcased as an example in this paper. Stakeholder engagement was utilised to estimate likely preferences and to conceptualise causal relationships of model parameters. The scenario modelling showed that a revolving loan fund supporting an energy performance contracting procurement procedure was preferred. Subsequently, the specific features of this preferred framework were optimised to yield the greatest number of viable retrofit projects over the long term. The results indicated that such a financing scheme would lead to substantial abatement of energy and water consumption, as well as carbon emissions. The strategic scenario analysis approach developed herein provides evidence-based support to policy-makers advocating novel financing and procurement models for addressing a government’s sustainability agenda in a financially responsible and net-positive manner.

The feasibility of reliably generating bioenergy from forest biomass waste is intimately linked to supply chain and production processing costs. These costs are, at least in part, directly related to assumptions about the reliability and cost-efficiency of the machinery used along the forestry bioenergy supply chain. Although mechanization in forestry operations has advanced in the last 20 years, it is evident that challenges remain in relation to production capability, standardization of wood quality, and supply guarantee from forestry resources because of the age and reliability of the machinery. An important component in sustainable bioenergy from biomass supply chains will be confidence in consistent production costs linked to guarantees about harvest and haulage machinery reliability. In this context, this paper examines the issue of machinery maintenance and advances in machine learning and big data analysis that are contributing to improved intelligent prediction that is aiding supply chain reliability in bioenergy from woody biomass. The concept of “Industry 4.0” refers to the integration of numerous technologies and business processes that are transforming many aspects of conventional industries. In the realm of machinery maintenance, the dramatic increase in the capacity to dynamically collect, collate, and analyze data inputs including maintenance archive data, sensor-based monitoring, and external environmental and contextual variables. Big data analytics offers the potential to enhance the identification and prediction of maintenance (PdM) requirements. Given that estimates of costs associated with machinery maintenance vary between 20% and 60% of the overall costs, the need to find ways to better mitigate these costs is important. While PdM has been shown to help, it is noticeable that to-date there has been limited assessment of the impacts of external factors such as weather condition, operator experiences and/or operator fatigue on maintenance costs, and in turn the accuracy of maintenance predictions. While some researchers argue these data are captured by sensors on machinery components, this remains to be proven and efforts to enhance weighted calibrations for these external factors may further contribute to improving the prediction accuracy of remaining useful life (RUL) of machinery. This paper reviews and analyzes underlying assumptions embedded in different types of data used in maintenance regimes and assesses their quality and their current utility for predictive maintenance in forestry. The paper also describes an approach to building ‘intelligent’ predictive maintenance for forestry by incorporating external variables data into the computational maintenance model. Based on these insights, the paper presents a model for an intelligent predictive maintenance system (IPdM) for forestry and a method for its implementation and evaluation in the field.

Electricity generation systems have traditionally been evaluated using only a limited number of economic or environmental indicators, for example capital investment, generation cost or carbon dioxide emissions. Moreover, the evaluations have generally been restricted to performance within the geographic boundary of the power station. This paper reports a sustainability assessment of power generation from Australian fossil fuels, notably black coal, brown coal and natural gas. A range of key sustainability indicators incorporating environmental, economic and social performance are included. The system boundary incorporates fuel extraction, fuel transport to the power station, generation of power, and transmission of electricity to the point of use. Most commonly employed existing technologies and some promising advanced technologies for power generation are considered. The cases of exporting Australian LNG and black coal to Japan for power generation in that country have also been considered. No one fuel or technology system was superior or inferior for every indicator. However the following generalizations can be made: Natural gas combined cycle systems have advantages for the majority of environmental and economic indicators, brown coal has an advantage in terms of value added, and black coal has relatively poor safety performance.

The integration of sustainable practices into infrastructure projects under the auspices of public-private partnerships (PPPs) is vital in the attainment of United Nation’s Sustainable Development Goals (SDGs). Since the inception of the SDGs in 2015, the attention of world has been shifting towards more sustainable practices and it is essential that the conventional performance measurement models on PPP projects also adapt to the trend of sustainable practices. Therefore, This study aims at reviewing and operationalising sustainable performance measures for the PPP infrastructure projects. A systematic literature review (SLR) methodology was utilised in this study. The research process began with the search, retrieval and selection of thirty-three (33) journal articles. Thoroughly, the selected articles were contently analysed to form key themes that form the basis of this research’s findings. The outcomes of this review demonstrate twenty-seven (27) most critical sustainable performance criteria of PPP projects such as the lowest project costs, green index, disability-friendly inclusion rate and carbon emission per project among others. Although, the study is limited to few journal articles, it provides theoretical and practical understanding of integration of sustainability in PPPs. Further, it gives a list of relevant research gaps for further studies. This study contributes to the benchmarking and management of sustainable performance assessment of PPP projects.

The design and assessment of net-zero buildings commonly focus exclusively on the operational phase, ignoring the embodied environmental impacts over the building life cycle. An analysis is presented on the consequences of integrating embodied impacts into the assessment of the environmental advantageousness of net-zero concepts. Fundamental issues needing consideration in the design process - based on the evaluation of primary energy use and related greenhouse gas emissions - are examined by comparing three net-zero building design and assessment cases: (1) no embodied impacts included, net balance limited to the operation stage only; (2) embodied impacts included but evaluated separately from the operation stage; and (3) embodied impacts included with the operation stage in a life cycle approach. A review of recent developments in research, standardization activities and design practice and the presentation of a case study of a residential building in Norway highlight the critical importance of performance indicator definitions and system boundaries. A practical checklist is presented to guide the process of incorporating embodied impacts across the building life cycle phases in net-zero design. Its implications are considered on overall environmental impact assessment of buildings. Research and development challenges, as well as recommendations for designers and other stakeholders, are identified.