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Building operations use 45% of the total energy in Australia, and Net-Zero Energy Buildings (NZEBs) are instrumental in achieving net zero emissions by 2050. However, research reveals that various factors hinder NZEB adoption in Australia, and it is imperative to contextualise the barriers, thereby highlighting clear gaps that can be addressed to enhance the implementation of NZEB in Australia. This study presents a systematic literature review and bibliometric analysis to examine the barriers that hinder the implementation of NZEB contextualised within the Australian building industry. The paper's novelty resides in its contextualisation of barriers to NZEB thereby highlighting clear gaps that can be addressed to enhance the implementation of NZEB in Australia. Emergent results reveal the most impactful barriers experienced and the inter-relatedness between barriers and their effects on each other. These identified barriers are also compared with comparable countries, including the UK, China, Italy and the US. New insight and knowledge acquired provide a basis for assessing potential solutions to the main barriers. Findings show that a lack of knowledge, climate issues, and cost issues, in addition to government policy factors, are considered primary barriers encountered by the industry, hindering the achievement of NZEBs. It is imperative that future studies and initiatives counteract these impacts to realise a better implementation of NZEB in the Australian context. [ABSTRACT FROM AUTHOR]

Emerging industries and technologies are made up of objective, practical requirements and ideas that encompass broad hopes for what future newness might enable. The bioeconomy is one such emerging industry. Its recent evolution has involved a complicated and dynamic mix of promises, reality checks and subsequent ambivalences. This article frames and investigates the emerging algae-based bioplastics industry as one niche within this broader system envisaged for social, technological, economic, political and ecological change. As such, our paper presents two categories of knowledge that in practice interrelate: 1) specific and practical recommendations that can assist a future algal-based bioplastics industry to develop in Australia in ways that are conscious of socio-ecological and socio-cultural dimensions, and 2) critical extensions that go beyond the attributes of newness, impact, suddenness and universality often emphasised in both popular and scientific research into emerging green technologies. In particular, our analysis highlights the importance of specific temporal, tonal and spatial factors when framing the contextual factors associated emerging industries, technologies and the different pathways for change they might help support. • Pathways and enabling factors for a algal-based bioplastics industry in regional Australia are presented. • The 'social idea' of the bioeconomy is analysed with reference to algal-based bioplastics. • The algal-based bioplastics industry is contextualised in relation to transition pathways literatureon the bioeconomy. • Themes and recommendations are synthesised from literature review and semi-structured interviews. [ABSTRACT FROM AUTHOR]

Australia is a long-term key partner of China in coal trading, which is famous for high-quality coal and its price advantage. However, affected by the evolution of international political and economic situation, China has issued a coal ban on Australian coal since the end of 2020. The potential environmental consequences of this coal ban remain unclear. So, this paper quantifies the ban's impact on air pollution, human health and climate change by simulating the emission difference between the port scenario (simulating the emissions due to Australian coal import under business as usual) and the mine scenario (simulating the emissions due to domestic coal mining that converted from import share of Australian coal), and monetizes the losses into economic costs for direct comparison. The results illustrate the emission of SO 2 , VOCs and GHG in mine scenario grows up to 102, 12 and 6 times the amount of that in port scenario, mainly deriving from coal mining process in the North China Plain and Yunnan-Guizhou Plateau. It shows that the potential alternative of replacing import with mining leads to PM 2.5 pollution exacerbation and O 3 pollution abatement, which causes 148 (95 % CI: 101–183) non-communicable diseases and respiratory disease-related deaths in total. As for GHG, the emission of BC in transportation process and fugitive methane in coal mining process contribute to an impressive effect on warming potential with few quantities, which is worth noting in control process. In total, the environmental deterioration resulted in an economic loss of approximately 934 million yuan. The undiminished demand for high-quality industrial coal as well as growing carbon tax could make the economic value of the coal ban's environmental consequences more considerable in the near future. This research emphasizes the contradiction between economic development and environmental improvement caused by excessive dependence on coal and addresses a critical knowledge gap in assessing the ban's environmental impact by economic value. The result directly demonstrates the environmental consequences of the potential mining-replacing-import alternative and helps better understand environmental influences on the Chinese government's decision. [ABSTRACT FROM AUTHOR]

Traditional glass bottles are the wine industry's major source of carbon emissions. Those wishing to reduce the carbon footprint embedded in wine have been looking to alternative packaging, such as PET, aluminium cans, and bag-in-box (BIB) to mitigate the impact. However, these alternative formats pose challenges with consumer acceptance and knowledge of the eco-benefits of each format. This paper uses a discrete choice experiment and latent class analysis to investigate the possible effects of message content and style (abstract vs concrete) on wine purchase in the context of brand size, brand prestige, and pricing. The analysis reveals the presence of two customer segments, which highly emphasise the pack format. Of the four non-glass packs tested, BIB and flat glass lookalike PET bottles score the highest preference after glass bottles. Message content and appeal type score low in their ability to alter preferences, whilst mid-to-low prices increase the chances of alternative packaging to be chosen. • Packaging format is a key choice driver for wine. • Glass is still the most preferred packaging format. • Bag in Box and low-carbon alternatives that look most like glass have the most potential for uptake. • Message content and appeal have little impact on choice. • Alternative packaging is more likely to be chosen for mid-to-low-priced wines. [ABSTRACT FROM AUTHOR]

Green buildings are synonymous with environmental sustainability; however, it is unclear what role its occupants, specifically employees, play in promoting sustainability in green office buildings. This paper proposes that Green Human Resource Management (HRM), underpinned by Social Identity Theory (SIT), can maximize the potential of green behaviors to improve employees' outcomes (e.g., job satisfaction and work-related flow) in green office buildings by creating positive workplace behaviors (i.e., green behaviors). We collected multisource data from 549 employees and 91 managers working in 17 organizations in green office buildings across Australia. We confirm the double mediation effects of Green HRM, green behaviors and organizational identification on the relationships between organizational readiness, job satisfaction and work-related flow. The paper makes theoretical contributions by advancing the concept of Green HRM and green behaviors within the realm of SIT, thus taking a multidisciplinary stance in the built environment and sustainability literatures. [ABSTRACT FROM AUTHOR]

Global concerns around climate change and the volatility of conventional fuel prices have prompted researchers and technologists to make significant efforts to identify and exploit alternative energy sources that are cleaner and more sustainable. Wind energy has seen considerable development among these alternative energy sources, mainly due to its abundance and global availability for extraction and the existing knowledge within the aviation and aerospace fields. Many nations, including European countries, already operate offshore wind farms (OWFs) and are progressively carrying out new projects and expanding on other projects. The Australian offshore environment provides unique opportunities for wind energy extraction, particularly along the southern coast of mainland Australia and the regions around Tasmania, where substantially strong winds blow most of the year. A significant challenge to establishing wind farms is the selection of site locations with optimal outputs. This can become a complex decision-making problem if there are numerous options and no information from previous projects. This paper aims to develop a decision-making framework to select the optimal location for installing OWFs while addressing financial, performance-related, and availability-related objectives. This paper adopts a game-theoretical approach to develop a decision-support tool to account for the interdependencies of influencing factors and possible conflicts amongst the parties. The game model is applied to an OWF development case study in the Bass Strait, known for its dominant and strong winds. • A framework to find the optimal location for installing Offshore Wind Farms (OWFs). • Game theory decision-making methodology for offshore renewable energy applications. • Define the influencing factors and conflicts amongst the interested parties. • Apply to OWFs development in Bass Strait, known for its dominant and strong winds. [ABSTRACT FROM AUTHOR]

The rapid urbanisation and infrastructure development projects have increased infinite property regeneration and construction projects in the developed countries. This study aims to examine the current construction waste management literature, including key authors, university networks, and relevant information systems, considering four selected countries, including Australia, Canada, the United Kingdom, and the United States. This paper uses a set of novel metrics, query-based search, and social network analysis techniques for evaluating a dataset of 2337 papers published in a decade by authors from different countries investigating the topic of recycling and reuse of construction and demolition waste in order to identify prominent researchers, influential universities, collaboration practices, and research trends. The dataset of publications is collected from Scopus and analysed using a set of network analysis techniques and statistical analysis. An additional dataset of keywords was collected from the Twitter pages of engineering firms and other relevant industry organisations to assess any possible connection between industry interests and research trends. In order to present a solid analysis of the current investigations in the field, a scientometric analysis along with a rigor statistical method was adopted to carefully identify trends, detailed sub-topics, and the materials investigated in the literature. A probit regression model for testing differences between countries in recycling practices was utilised in the STATA environment. The findings show a set of network analysis and clusters that can help scholars to set their future studies based on the current advances and limitations identified in the literature. Within the dataset, 42% of publications referred to concrete waste, whilst only 2.2% included glass, 2.5% included brick, 4.3% included steel and none included wood, which shows the most common building materials have not been fully covered in the literature. Only 48 publications, or 7.4% of the dataset, originated from the three selected concrete-focused journals. It was also found that information systems appeared in the database lately; however, there is less discussion in the literature on how the integration of Geographic Information System (GIS), Buidling Information Model (BIM), 3D Printing and geo-spatial data analysis can help waste management in the field of construction. The bibliographic analysis of the selected cases shows that universities in Canada and the US exhibit more evidence of domestic collaboration and industry partnerships than universities in Australia and the UK. Additionally, there is evidence to suggest that publications with at least one industry co-author are more likely to address the issue of regulation. The outcome of this paper enables academics, engineers, and regulators to predict research trends, improve industry collaborations and utilise information systems and assign more research resources to address the identified gaps in the literature. • Developed a network of 1408 authors within the dataset and apply Total Publications metrics. • Examined the collaboration of 529 institutions within Australia, Canada, the UK, and the US. • Utilised a probit regression model for testing differences between countries in recycling practices. • Visualised an online GIS-based dashboard of landfills and recycling facilities using geo-spatial data. • Identified gaps in two different directions of material technology and management systems. [ABSTRACT FROM AUTHOR]

The increasing awareness of the undesirable environmental impact of cement-based products has led to rethinking earth construction within the digitally mechanised framework of Industry 4.0. The attempts to mechanise earth construction started nearly a decade ago, yet, the past four years have seen a surge in the intensity of research on the advanced manufacturing of earth construction. Additive manufacturing of clay-rich soil, like in cob and adobe methods, has been attracting the primary attention, while on the contrary, considerably limited research has been conducted to mechanise other methods such as rammed earth. This paper collected, reviewed, and analysed the state-of-the-art research on the advanced manufacturing of rammed earth construction, with a focus on process design aspects and machine development. Two case studies of recent digitally manufactured rammed earth projects in Australia and Switzerland were comprehensively analysed to provide a realistic feasibility assessment of the potential and technical challenges. The insights from this research provide a holistic and tangible roadmap to the digital manufacturing of rammed earth construction, which aids in making it more desirable and capable of meeting contemporary demands of the architecture and construction of Industry 4.0. • State-of-the-art advanced manufacturing methods for rammed earth construction are critically reviewed. • Two case studies of digitally manufactured rammed earth projects in Australia and Switzerland are comprehensively analysed. • Potential and challenges of advanced manufacturing for rammed earth construction are discussed. • Information for enhanced utilisation of digital techniques in rammed earth construction is provided. [ABSTRACT FROM AUTHOR]

This paper investigates the least-cost greenhouse gas (GHG) abatement pathway for a coupled energy system. We consider the roles of diverse abatement technologies, such as renewable electricity generation, biomass and carbon capture and storage (CCS), as well as sources of operational flexibility, such as peaking generators, electricity storage, transmission and electrolysis. Scenario and sensitivity analyses are applied to explore plausible pathways to energy system decarbonization. All modelled pathways to a zero-emissions energy system feature an accelerating transition from fossil fuels to renewable energy with diverse technologies playing a role. This includes variable renewable generators (VRG), CCS, and sources of operational flexibility on different timescales. Specifically, synchronous condensers appear to be a cost-effective option to control system frequency, inter-seasonal hydrogen storage in engineered caverns can play a significant and complementary role to that of pumped hydro and battery storage, and technologies that capture and sequester atmospheric carbon, including biomass-to-CCS and direct air capture (DAC), can also play a significant role in the transition to net-zero emissions. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) or particle pollution include the tiny particles of dust and fly ash particles are expelled from coal-burning power plants. Coal combustion is an extremely prevalent source of air pollution, and resulting PM has substantial impacts on human health, especially in industrial zones. This paper aims to design a novel hybrid deep learning framework based on long short-term memory (LSTM) integrated with a two-stage data filtering technique to accurately predict the air quality indices (i.e., PM 2.5 and PM 10) in a chosen study region 'Miles Airport, Queensland,' that meets the needs of the coal seam gas industry in Australia. The data used to construct the novel hybrid two-stage data filtering technique based on LSTM comprising of six meteorological parameters (i.e., wind direction, wind speed, air temperature, relative humidity, solar radiation, and rainfall) and two environmental factors (i.e., ozone and total suspended particulate). In the first stage, two robust feature selection methods, namely, extreme gradient boosting (XGBoost) and the classification and regression tree (CART) approach, were adopted to explore the most significant predictors. Then in the second stage, the best subset regression (BSR) technique is utilized to determine the best subsets input combinations i.e., C1, C2, and C3 based on several particular metrics. The three BSR-based input combinations were employed in the LSTM model to estimate the PM 2.5 and PM 10. Furthermore, to validate the main hybrid framework, two advanced machine learning (ML) methods (i.e., LightGBM and ridge kernel regression (KRR)) and two traditional ML methods (i.e., Adaptive neuro-fuzzy inference system (ANFIS) and multilayer perceptron neural network (MLP)) were hybridized with the multi-level data filtering strategy by examining the optimal input combinations. Several statistical metrics, graphical tools, and diagnostic analyses evaluated the hybrid models. The outcomes of the PM 2.5 simulation based on 2375 data samples showed that the LSTM-C3 containing all the selected predictors yielded the most promising accuracy, followed by the LightGBM-C3 and MLP-C3 models. On the other hand, the simulation of PM 10 distribution demonstrated that the LSTM-C3 was superior to other models, followed by the KRR-C3 and LightGBM-C3 models. [ABSTRACT FROM AUTHOR]

There is growing consensus that to effectively respond to the urgency of the global climate emergency we require a new model of what it means to be sustainable. Regenerative development provides a compelling alternative by seeking to realign our efforts in a participatory and co-evolutionary relationship with nature to create the conditions necessary for a healthy life into the future. Practical applications of regenerative development have therefore begun to emerge, especially at a precinct scale. However, few studies have investigated the underlying processes and decisions that have enabled their emergence. This paper conducts a qualitative investigation into the decision-making approaches of four case study precincts across Australia that are aligned with regenerative development to provide the foundation to inform future decision-making practices in the built environment. Key findings of this investigation are presented as themes that help provide an understanding of the key decisions that can enable a precinct to achieve its positive value adding potential. These key findings are seen as an important first step towards informing the future development of a decision-making framework for regenerative precinct development. [ABSTRACT FROM AUTHOR]

This study considers the emissions implications of co-combusting imported ammonia in coal-fired power stations. The study adopts a supply chain approach, estimating the emissions reduction potential of 20% ammonia co-combustion in coal-fired power stations in the country of use, and the emissions associated with ammonia production in the country of origin. The paper considers the emissions implications of using different ammonia production technologies: Haber-Bosch (HB) ammonia production with hydrogen generated from steam methane reforming using natural gas (SMR), with and without carbon capture and storage (CCS); Haber-Bosch ammonia production with hydrogen generated from renewable sources; and fully renewable electricity generated ammonia. The empirical setting of the study is an ammonia supply chain encompassing Japan and Australia. The results show co-combustion of ammonia produced with SMR-HB provides no net benefit for the combined country emissions, as ammonia production related greenhouse emissions in Australia are equivalent to the emission reductions in Japan. In contrast, co-firing ammonia produced from fully renewable sources reduces emissions in the two countries in 2030 by 43 MT per annum. SMR-HB processes with varying levels of CCS reduce annual emissions by 16–34 MT. Based on the results, different policy options are suggested for managing the emissions associated with a Japan-Australia ammonia supply chain. • Japan actively pursuing ammonia/coal co-combustion to reduce power sector greenhouse gas emissions. • An Australia-Japan ammonia supply is examined at a country boundary emissions basis. • Choice of ammonia manufacturing approach has significant impact on emissions. • 40 MT pa saving in Japan offset by 39 ± 11 MT pa increase in Australia from Best Available Technology. • Only a fully renewable ammonia manufacturing process reduces emissions in both Australia and Japan. [ABSTRACT FROM AUTHOR]

The electrification of large-scale bus depots will bring challenges for bus depot operators (BDOs) aiming to minimize operational costs. A potential solution for BDOs managing electric buses (EBs) with large batteries that are capable of vehicle-to-grid (V2G) operational functionalities, along with on-site generation facilities, is to actively participate in the energy market. This paper proposed a novel two-stage multi-objective stochastic optimization-based energy management system (EMS) for BDOs to trade energy in a day-ahead (DA) energy market while considering the expected cost of energy imbalances in the real-time (RT) market. The optimization model for charge–discharge scheduling is based on a mixed-integer linear programming approach. The uncertainties associated with the DA forecast are complemented by a stochastic model. Minimizing the cost of electricity and the penalty costs for battery capacity degradation are the objectives that need to be met simultaneously. The proposed EMS is evaluated using simulation studies considering a hypothetical bus depot in Australia. The effectiveness of the proposed EMS for overall financial savings is validated by comparing its performance with state-of-the-art scheduling strategies. Results show that the net energy cost for the proposed EMS is 38% lower compared to a deterministic scheduling strategy that does not allow V2G flexibilities, 33% lower compared to a deterministic scheduling strategy that allows V2G flexibilities and 17% lower compared to a stochastic scheduling strategy that minimizes overall costs. [ABSTRACT FROM AUTHOR]

Due to significant weather variabilities of rainfalls, potential water savings through rainwater tanks are expected to vary significantly. Moreover, within some large cities, significant spatial variations are reported. With the emerging impacts of climate change, existing weather and spatial variabilities of potential water savings are also likely to be changed, which are unknown to the end-users. This paper presents the impacts of climate change on current weather and spatial variabilities of potential water savings for Adelaide, a large city in Australia. Future daily rainfall data was collected from a data portal provided by the Australian government derived through a statistical downscaling modelling. Projected daily rainfall data was fed to an earlier developed daily water balance model (eTank) to calculate water savings for three future periods; 2030–2050, 2055–2075 and 2080–2100. Three weathers (dry, average and wet) in each period were considered along with two climate change scenarios (RCP 4.5 and RCP 8.5) and two tank sizes (5 kL and 10 kL). It is found that varying outcomes without any general trend are expected depending on the projection scenario, period and weather condition. Contrary to the general perception, it is found that in several cases, the potential water savings are expected to increase compared to the current climate. Most of those expected increases in water savings are attributed to the projection scenario of RCP 4.5, in the near future and in dry years. In the far-future and with the projection scenario of RCP 8.5, most of the potential water savings are expected to decrease compared to the current climate. Regarding changes in spatial variability of water savings, it is found that the spatial variability will decrease in the near future, but will increase towards the far future. [ABSTRACT FROM AUTHOR]