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In this work we assess the pathways for environmental improvement by the coal utilization industry for power generation in Australia. In terms of resources, our findings show that coal is a long term resource of concern as coal reserves are likely to last for the next 500 years or more. However, our analysis indicates that evaporation losses of water in power generation will approach 1000 Gl (gigalitres) per year, equivalent to a consumption of half of the Australian residential population. As Australia is the second driest continent on earth, water consumption by power generators is a resource of immediate concern with regards to sustainability. We also show that coal will continue to play a major role in energy generation in Australia and, hence, there is a need to employ new technologies that can minimize environmental impacts. The major technologies to reduce impacts to air, water and soils are addressed. Of major interest, there is a major potential for developing sequestration processes in Australia, in particular by enhanced coal bed methane (ECBM) recovery at the Bowen Basin, South Sydney Basin and Gunnedah Basin. Having said that, CO2 capture technologies require further development to support any sequestration processes in order to comply with the Kyoto Protocol. Current power generation cycles are thermodynamic limited, with 35-40% efficiencies. To move to a high efficiency cycle, it is required to change technologies of which integrated gasification combined cycle plus fuel cell is the most promising, with efficiencies expected to reach 60-65%. However, risks of moving towards an unproven technology means that power generators are likely to continue to use pulverized fuel technologies, aiming at incremental efficiency improvements (business as usual). As a big picture pathway, power generators are likely to play an increasing role in regional development; in particular EcoParks and reclaiming saline water for treatment as pressures to access fresh water supplies will significantly increase.

Abstract With emphasis on application in the built environment, this paper analyses meanings of the term ‘solar energy use’. It shows that failure to address the inherently vague and context dependent nature of the concept leads to much confusion, especially when attempts at absolute quantification are made. The paper argues that meaningful absolute quantification of solar energy use is impossible, and that misplaced attempts at this quantification have serious implications, especially in relation to decisions at the level of government policy. To avoid confusion, solar energy should not be considered as a component of conservation, energy-efficiency, or renewables, and definition and quantification of solar energy use should be qualified regarding purpose of quantification, type of energy, definition of use, baselines and context.

Abstract This paper is based on dynamic optimization methodology to investigate the economic energy efficiency issues in developing countries. The paper introduces some definitions about energy efficiency both in economics and physics, and establishes a quantitative way for measuring the economic energy efficiency. The linkage between economic energy efficiency, energy consumption and other macroeconomic variables is demonstrated primarily. Using the methodology of dynamic optimization, a maximum problem of economic energy efficiency over time, which is subjected to the extended Solow growth model and instantaneous investment rate, is modelled. In this model, the energy consumption is set as a control variable and the capital is regarded as a state variable. The analytic solutions can be derived and the diagrammatic analysis provides saddle-point equilibrium. A numerical simulation based on China is also presented; meanwhile, the optimal paths of investment and energy consumption can be drawn. The dynamic optimization encourages governments in developing countries to pursue higher economic energy efficiency by controlling the energy consumption and regulating the investment state as it can conserve energy without influencing the achievement of steady state in terms of Solow model. If that, a sustainable development will be achieved.

Abstract Since the adoption of the Kyoto protocol in 1997 and its entry into force in 2005, as well its aftermath such as the Doha amendment and Paris agreement, national policies have become more conscious of the usage of clean energy, mostly the different forms of renewable energy and nuclear energy. Ratifying countries and signatories had committed themselves to binding targets for the reduction of greenhouse emissions by 8% with respect to 1990 levels until 2012, also based on the particular contribution to global emissions from each country. This paper examines the integrational properties of clean energy consumption from eight emerging economies which are also high greenhouse gas emitters. The empirical results show that the clean energy consumption is stationarity for Brazil and Philippines by using a quantile unit root test without smooth breaks (Koenker and Xiao, 2004). However, after capturing the smooth breaks (Bahmani-Oskooee et al., 2018), we find the clean energy consumption of China, Pakistan and Thailand are stationary. The time-varying deterministic trend with smooth breaks is more fitted to the path of clean energy consumption in comparison to the deterministic trend without smooth breaks. The paper suggests economic insights useful for policy making.

Abstract The urge to increase renewable energy penetration into the power supply mix has been frequently highlighted in response to climate change. South Korea was analyzed as a case study for which the government has shown motivation to increase renewable energy penetration. Herein, a hybrid renewable energy system (HRES) including solar and wind energies were selected due to their relatively stable and mature technology. In addition, Power-to-X has been incorporated to cover other renewable energy options such as hydrogen and synthetic natural gas (SNG). Therefore, an approach of forecasting the weather characteristics and demand loading over a relatively long timeframe was implemented via deep learning techniques (LSTM and GRU) and statistical approaches (Fbprophet and SARIMA), respectively. A deployment strategy incorporating HRES and Power-to-X is then proposed in correspondence to the forecasted results of the 15 regions considered in this study. An extension of this, the reliability of the designed system is further assessed based on the probability of the demand losses with the aid of Monte-Carlo simulation. With the proposed deployment strategy, a total annual cost of 9.88 × 1011 $/year and a greenhouse gas reduction of 1.24 × 106 tons/year are expected for a 35% renewable energy penetration. However, only SNG shows relatively competitive cost (at 23.20 $/m3 SNG), whereas the average costs of electricity (0.133 $/kWh) and hydrogen (7.784 $/kg H2) across the regions are yet to be competitive compared to the current market prices. Nonetheless, the priority of deployment across regions has been identified via TOPSIS.

Abstract We evaluated three Integrated Assessment Models (IAMs: IGSM, MERGE, MiniCAM) by: (i) comparing their global Primary Energy year-2000 initializations and projections for 2010 and 2015 to historical data; (ii) mapping their CO2 emissions projections against observations; and (iii) examining model-output diagnostics. The IAMs underestimated historical primary energy consumption and initial/projected CO2 emissions in both reference and stabilization scenarios (particularly for combustion fuels) but overestimated usage of non-biomass renewables, causing underestimates of future CO2 emissions that, for the stabilization scenarios, are wildly optimistic. Mitigation technology breakdowns in the policy scenarios vary enormously across IAMs, suggesting that confidence in their projections might be misplaced, or that options for mitigation have greater scope than is supposed. Most increases in carbon-free technologies in the stabilization scenarios are already captured in the reference cases. Energy-conversion efficiencies in electricity generation improve over time, but, (except for gas-powered generation in IGSM), efficiencies in the policy scenarios are less than in the reference. Electrification results diverge widely: IGSM has little change over the 21st century, while MiniCAM and MERGE have major electrification increases in their policy scenarios. We suggest: 1) comprehensive model output suitable for secondary analysis should be more readily available; 2) directly comparable reference and policy-driven mitigation scenarios are essential for assessing mitigation measures; 3) model validation using historical, source-specific energy data is crucial for assessing model credibility; 4) separation of mitigation contributions into no-policy and policy-driven amounts is needed to assess the effectiveness of mitigation policies; and 5) detailed inter-model comparisons can provide important insights into model credibility.

Abstract: After the implementation of a biofuel target in 2017, China, the second largest consumer of oil in the world, accelerated the development of lignocellulosic biomass technology to produce ethanol and minimized food security risks commonly associated with first generation biofuel production. In this study, Life Cycle Assessment (LCA) is used to investigate three new lignocellulosic biomass refinery systems based on corncob which co-produce ethanol with chemicals and energy. The bioethanol is used in E10 and E85 biofuel mixes and these are compared with a fossil gasoline reference system. Using 1 km distance driven by a compact size flexible fuel passenger vehicle as the functional unit and a exergy allocation approach to the raw material inputs and to the co-products in the simulated multifunctional biorefinery processes, the results indicate that regardless of the configuration of the ethanol-biorefinery, ethanol-blended fuels performed better than gasoline in terms of fossil fuels depletion (E10 6% lower; E85 64–70% lower), global warming potential (E10 1–10% lower; E85 5–113% lower) and human toxicity potential (E10 6–7% lower; E85 72–75% lower), but worst in terms of ozone layer depletion (E10 4.5–6.8 times higher; E85 51.9–78.2 times higher), acidification (E10 30–50% higher; E85 3.3–5.5 times higher) and eutrophication potential (E10 5.2–7.0 times higher; E85 42.4–64.0 times higher) than gasoline.

Although considered a current highlight, the concept of intelligent buildings (IB) has not been adopted as quickly and widely as expected. One of the reasons for this is the lack of information and knowledge support to all professionals involved at the design stage of a project. This paper provides a brief overview on the new advances of IB technologies and discusses ways of supplementing the decision making process by adopting two methods for economical and technical aspects of IB applications. It goes on to introduce an on-going research which aims to utilise knowledge based systems to provide comprehensive evaluations to alternatives and decision support to retrofit building projects, when they are being conceptualised.

Abstract To understand the relationship between green building energy performance and regional commercial estates, this study analysed Australia’s Commercial Building Disclosure (CBD) program database. This database discloses the annual energy use intensity (EUI) and the corresponding energy rating (1–6 stars) of 2460 National Australian Built Environment Rating System (NABERS) certified office buildings. The study selected for analysis Australia’s six largest cities and then used panel data regression, where commercial estate factors (total stock of office buildings, vacancy rate, average gross face rent, and government incentives such as financial support) served as independent variables and the EUI was the dependent variable. The p-values of all the models are below 0.05, indicating that the results are statistically significant. Results showed the commercial real estate factors were significantly related to the EUI for buildings with a rating of 1 star and above. The correlation between EUI and commercial real estate factors became less strong with the rating level increasing. The effect of ‘green building’ branding makes the office buildings more attractive with regard to tenancy and their energy performance more reflective of the variation in the commercial real estate market. This study is a frontrunner in contextualising green building energy performance and ratings in the context of regional commercial estate, and the regression models employed in the study could be used to define regional baselines for energy ratings in future studies.