• Energy Research
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Co-generation of energy derived from human movement is not new. Intentionally accumulating energy, from mass urban-mobility, provides opportunities to re-purpose power. However, when mass-mobility is predictable, yet not harnessed, this highlights critical gaps in application of interdisciplinary knowledge. This research highlights a novel application of geostatistical modelling for the built environment with the purpose of understanding where energy harvesting infrastructure should be located. The work presented argues that advanced Geostatistical methods can be implemented as an appropriate method to predict probability distribution, density, clustering of populations and mass-population mobility patterns from large-scale online distributed and heterogeneous data sets published by the Australian Urban Research Infrastructure Network. Where clear urban spatio-behavioural relationships of density and movement can be predicted – understanding such patterns supports cross-disciplinary city planning and decision-making. A data-informed – predictive spatial decision-making framework is proposed – facilitating the endeavour of cogenerating kinetic human energy within a prescribed space. This novel proposition could further sustainability strategies for compact living for cities such as in Perth, Western Australia which is increasingly economically and geographically pressured to densify. This research argues that surveillance data elucidate a capacity to interpret and understand impacts of densification strategies, efficacy of CCTV networks in existing and emerging cities.

The COVID-19 pandemic has impacted all sectors of the tourism industry, particularly air transportation. However, air transport remains an important contributor to economic growth globally. Thus, this study examines whether air transport (a proxy for tourism) stimulates economic growth to validate the air-transportation-led growth hypothesis (ALGH) in the Australian context. To conduct the study, we analyse the asymmetric long-run and short-run impacts of the air passengers carried (a proxy for tourism) on the gross domestic product (GDP) in Australia. We use the nonlinear autoregressive distributed lag (NARDL) modelling approach on data for Australia from 1971 to 2019. We also examined the effects of selected control variables (i.e., energy consumption, financial development, socialisation, and urbanisation) on economic growth. In both the short and long run, we observed statistically significant asymmetric impacts of air transport on economic growth. The positive shocks in air transport propel the long-term growth of Australia’s economy. Additionally, according to the findings, negative shocks of air transport have a stronger detrimental impact on economic development than positive shocks.

A reasonable plan for charging stations is critical to the widespread use of electric vehicles. In this paper, we propose an optimal planning method for electric vehicle charging stations. First of all, we put forward a forecasting method for the distribution of electric vehicle fast charging demand in urban areas. Next, a new mathematical model that considers the mutual benefit of electric vehicle users and the power grid is set up, aiming to minimize the social cost of charging stations. Then, the model is solved by the Voronoi diagram combined with improved particle swarm optimization. In the end, the proposed method is applied to an urban area, simulation results demonstrate that the proposed method can yield optimal location and capacity of each charging station. A contrasting case is carried out to verify that improved particle swarm optimization is more effective in finding the global optimal solution than particle swarm optimization.

Research to date has suggested that both individual marine species and ecological processes are expected to exhibit diverse responses to the environmental effects of climate change. Evolutionary responses can occur on rapid (ecological) timescales, and yet studies typically do not consider the role that adaptive evolution will play in modulating biological responses to climate change. Investigations into such responses have typically been focused at particular biological levels (e.g., cellular, population, community), often lacking interactions among levels. Since all levels of biological organisation are sensitive to global climate change, there is a need to elucidate how different processes and hierarchical interactions will influence species fitness. Therefore, predicting the responses of communities and populations to global change will require multidisciplinary efforts across multiple levels of hierarchy, from the genetic and cellular to communities and ecosystems. Eventually, this may allow us to establish the role that acclimatisation and adaptation will play in determining marine community structures in future scenarios.

The combination of car-sharing and electric vehicles can increase the acceptance of electric vehicles and facilitate car-sharing to be a more sustainable means of transport. However, this also poses more challenges for the good planning of electric car-sharing systems. To assist car-sharing companies in improving the planning decisions, this paper developed an evaluation framework from a comprehensive view. In the first step, four evaluation criteria were identified according to the planning process: construction of stations; routine inspection; vehicle usability and relocation management; and the maintenance and replacement of stations. Then, a combinatorial method based on analytic hierarchy process (AHP), cost-benefit analysis (CBA), and Voronoi diagram (VD) is developed to determine the relative weight of the four criteria and evaluate the alternative. Finally, the evaluation framework was applied in a realistic case of EVCARD, which is the most influential electric car-sharing company in China. The performance of two different operational districts of EVCARD—Jingan and Changning—were compared. The results showed that vehicle usability and relocation management is the greatest criterion influencing the planning performance of the electric car-sharing system in China, and that routine inspection is a negligible but important factor. According to the relative scores, Jiagan District performed better than Changning district.

This paper explores institutional responses from Regional Fisheries Bodies (RFBs) to climate change. Fisheries management is highly dependent on the stability or predictability of targeted fish populations. Oceanic changes occurring as a result of climate change will see continuing and potentially irreversible deviations from the conditions of fisheries past. These changes present challenges to fisheries management at all scales – from local to international – relating to food security, sustainability, and ecological integrity. Areas of measurably warmer ocean, or ‘hotspots’, are a very clear indicator of direct climate change effects. RFBs with hotspots in their areas of competence were chosen for this study. Three levels of institutional engagement were developed: Awareness of climate change; Learning about climate change; Action taken by the institutions. While 94% of institutions demonstrated awareness of climate change and 82% demonstrated learning about climate change, only 41% demonstrated some form of action; and these were mainly procedural and administrative. Only two of the RFBs considered made explicit statements about incorporating climate change into future fishing management plans. The inference is that RFBs are largely practising business-as-usual, with the implication that many exploited fish populations will face additional survival pressure as the sea around them alters.