• Energy Research
• 7. Clean energy close
• 11. Sustainability close
• 3. Good health close
• AU close
• Transport Research close

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

Twenty-minute neighbourhoods highlight the importance of well-connected and mixed-used neighbourhoods and communities with proximate access to employment, essential services, public transport, and open spaces. Shorter distances together with re-prioritised public spaces encourage more active transport choices, resulting in public health benefits and reduced environmental pollution. Higher liveability brought about by mixed-use developments enables people to have equitable access to local facilities, amenities, and employment opportunities, promoting vibrancy, social cohesion, and intergenerational connections. The attributes of 20-minute neighbourhoods also combine to create places, that are acknowledged as friendly for all ages, address changing needs across the life course, and provide better support for the ageing population. Furthermore, there are indications that 20-minute neighbourhoods may be more resilient against many of the negative impacts of stringent public health protocols such as those implemented in periods of lockdown during the Covid-19 pandemic. In this article, we evaluate and compare planning policies and practices aimed at establishing 20-minute neighbourhoods in Melbourne (Australia) and Scotland (the UK). Using case studies, we discuss similarities and differences involved in using place-based approaches of 20-minute neighbourhoods to address 21st-century challenges in key areas of health and wellbeing, equity, environmental sustainability, and community resilience.

As connected, electric, and autonomous vehicle (AV) services are developed for cities, the research is conclusive that the use of these services must be shared to achieve maximum efficiency. Yet, few agencies have prioritised designing an AV system that focuses on dynamic ridepooling, and there remains a gap in the understanding of what makes people willing to share their rides. However, in 2017, the Australian transport authority Transport for New South Wales launched over a dozen trials for on-demand, shared public transport, including AVs. In this paper, we investigate the user willingness-to-share, based on experiences from one of these trials. Four focus groups (19 participants in total) were held in New South Wales with active users of either the trialled on-demand dynamic ridepooling service (Keoride) or commercial ridepooling (UberPool). Through thematic analysis of the focus group conversations, the cost, comfort, convenience, safety, community culture, and trust in authority emerged as factors that influenced the willingness-to-share. When presented with driverless scenarios, the focus group participants had significant concerns about the unknown behaviour of their co-passengers, revealing sharing anxiety as a significant barrier to the adoption of shared AVs. This paper identifies previously disregarded factors that influence the adoption of AVs and dynamic ridepooling and offers insights on how potential users’ sharing anxiety can be mitigated.

Public transport is a cornerstone in the transition towards sustainable cities. Moreover, greenhouse gas emissions can be further reduced through powertrain electrification. In this context, plug-in electric hybrid buses emerge as a suitable and flexible solution. They can switch between an electric motor and a combustion engine during operation. An optimal electric drive assignment strategy allows achieving a high electric range and reduced tailpipe emissions. In this work, we look for optimal strategies for maximizing the distance traversed in electric mode and minimizing the total emissions, for real routes including green corridors where the combustion engine cannot be used. Contrary to existing works, this approach does not only focus on the improvement of the bus performance in terms of energy consumption, but also on the environmental benefits and livability of cities. This challenge is solved using two multi-objective state-of-the-art evolutionary algorithms, and a novel heuristic, GreenK. Two real- world scenarios are analyzed, namely bus routes M6 in Badalona, and 18 in Grudziadz. Results show a significant reduction in emissions of up to 21% with respect to the strategy found by GreenK, meaning 24 kg less pollutants emitted daily and over 22.5% electric range increase, compared to the currently deployed solution

Urban rail transit (URT) systems are critical to modern public transportation services. Unfortunately, disruptions in URT systems can lead to dysfunction and threaten sustainable development. This study analyses URT network sustainability from a vulnerability perspective. Two network attack scenarios, including random attacks and intentional attacks, are designed to assess different kinds of disruptions to URT networks. Under random attacks, nodes are randomly removed from the network. In contrast, under intentional attacks, key nodes are identified and removed based on topological metrics and passenger flow volume. Then, URT network vulnerability is evaluated by quantifying the changes in network efficiency and structural integrity under the network attacks from a spatio-temporal point of view. The real-world case of the Shanghai URT system from 1993 to 2020 is used to illustrate the vulnerability in the evolution of the URT system. The results indicate that the URT network is increasingly fault-tolerant and structurally robust over time. The URT network is more vulnerable to intentional attacks than to random failures. Additionally, there are significant spatial differences in the vulnerability of Shanghai URT network. Stations in the central activity zone (CAZ) are more fault-tolerant and robust than stations located outside of the CAZ. Furthermore, stations with large centrality and greater passenger flow volumes and lines with many key nodes and greater passenger flow volumes, are vulnerable to disruptions in the URT networks. This study provides a new index to comprehensively quantify node centrality; it also fills a research gap by analysing the vulnerability of URT networks based on both longitudinal and spatial patterns. Finally, this paper highlights significant practical implications for the sustainable development of URT networks, as well as the sustainable development of public transportation services.

We present findings from a geotechnical survey for a gravity-based Wave Energy Converter (WEC) to be installed in King Island, Tasmania. The goal of this work was to assess the deployment location for a 200 kW Oscillating Water Column (OWC) and to identify possible challenges for the foundation of the structure to make it Australia’s first operational offshore OWC for a remote offshore island. The proposed location for this OWC is the southeast coast of King Island, Tasmania, approximately in a depth of ~5.5 m LAT. The survey included sub-bottom profiling, sediment cores, surficial sediment strength by penetrometer drops, seabed imagery, as well as long-term deployment (>6 months) of pressure sondes and an acoustic wave current profiler (AWAC). Our findings demonstrate that the WEC can be installed in the proposed location with significant wave height Hs ~1–1.5 m and peak period Tp of 12–14 s, and that the site exhibits sufficient sand coverage and quasisteady bearing capacity. The period between the survey and prospective deployment is only one year, demonstrating the efficiency of the survey methods (in particular, the use of the penetrometer) and OWC design but also the suitability of the candidate site for this device design.

Particle number, particle mass, and CO2 concentrations were measured on the curb of a busy urban busway used entirely by a mix of diesel and CNG operated buses. With the passage of each bus, the ratio of particle number concentration and particle mass concentration to CO2 concentration in the diluted exhaust plume were used as measures of the particle number and mass emission factors, respectively. With all buses accelerating pastthe monitoring point, the results showed that the median particle mass emission from CNG buses was less than 9% of that from diesel buses. However, the median particle number emission from CNG buses was 6 times higher than the diesel buses, and the particles from the CNG buses were mainly in the nanoparticle size range. Using a thermodenuder to remove the volatile material from the sampled emissions showed that the majority of particles from the CNG buses, but not from the diesel buses, were volatile. Approximately, 82% of the particles from the CNG buses and 38% from the diesel buses were removed by heating the emissions to 300 degrees C.

One of the most encouraging sorts of renewable energy is ocean wave energy. In spite of a large number of investigations in this field during the last decade, wave energy technologies are recognised as neither mature nor broadly commercialised compared to other renewable energy technologies. In this paper, we develop and optimise Power Take-off (PTO) configurations of a well-known wave energy converter (WEC) called a point absorber. This WEC is a fully submerged buoy with three tethers, which was proposed and developed by Carnegie Clean Energy Company in Australia. Optimising the WEC’s PTO parameters is a challenging engineering problem due to the high dimensionality and complexity of the search space. This research compares the performance of five state-of-the-art metaheuristics (including Covariance Matrix Adaptation Evolution Strategy, Gray Wolf optimiser, Harris Hawks optimisation, and Grasshopper Optimisation Algorithm) based on the real wave scenario in Sydney sea state. The experimental achievements show that the Multiverse optimisation (MVO) algorithm performs better than the other metaheuristics applied in this work.