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Seawater desalination is an important option for addressing the world's water supply challenges. Current desalination plants use enormous quantities of energy and cause a number of environmental issues. Renewable energy options, mostly solar and geothermal systems, have been examined in detail to supply the energy needed for water desalination. The co-location benefit of energy derived from the ocean to power seawater desalination processes is appealing. However, the promise and potential of ocean-based power generation for desalination systems has not been investigated in detail. The development of such systems has been limited due to technological and economic limitations of energy harvesting and transport as well as device maintenance under water. In this paper, we review the state of the art of ocean energy in desalination. It explores different sources of energy from the ocean that include electricity generation, as well as mechanical force and thermal energy and salinity gradients that can also be directly harnessed for powering the desalination processes. We also examine recent advances in scaling up for commercial deployment, and discuss relevant cost, environmental and social concerns. The great potential of ocean energy for seawater desalination in terms of diverse energy forms, flexible integration methods and various deployment strategies can provide important environmental, water and social benefits for seawater desalination, thus promote sustainability in water-energy nexus. The use of ocean energy in desalination applications could benefit the future development of ocean energy technology in renewable energy sector.

AbstractIn this research we propose a physical measure of resource efficiency, based on exergy, which combines energy and material flows in a single dimensionless metric, bounded by 0 and 1. The inclusion of materials in the efficiency metric makes it possible to compare a wide range of industrial devices and processes, and even different sectors, using a consistent framework. Resource efficiencies for steel-making processes were computed as an example and were found to range from 10.0% in sinter plants to72.1% in coke ovens. A unified resource efficiency measure helps identify the drivers of resource consumption and reveal opportunities to reduce carbon emissions.

This article investigates how real estate stakeholders price information conveyed by voluntary environmental certification schemes in Sao Paulo, the largest metropolitan area of Latin America. In addition to low incidence of green buildings, the city and many local urban agglomerations in Brazil exhibit weak environmental performance due to limited capacity to enforce existing regulation. Therefore, we exploit the role of internationally accredited third-party environmental audit schemes. In addition to comparing labelled and non-labelled properties in a hedonic framework, we also examine pricing discrepancies related with the intention to certify (registration), but no achievement of actual certification in a timely manner. Our results systematically indicate that labelled office properties in Sao Paulo yield a larger green premium than their peers from developed countries. Findings also suggest that applicants who do not obtain the label upon delivery do not receive any green premiums and may be subject to discounts, depending on specification, beyond that of other non-green office buildings. These findings provide further evidence of the relevance of market diffusion and economic governance linked to the implicit pricing of environmental labels.

AbstractThe production of clean fuels and chemicals from waste feedstocks is an appealing approach towards creating a circular economy. However, waste photoreforming commonly employs particulate photocatalysts, which display low product yields, selectivity, and reusability. Here, a perovskite‐based photoelectrochemical (PEC) device is reported, which produces H2 fuel and simultaneously reforms waste substrates. A novel Cu30Pd70 oxidation catalyst is integrated in the PEC device to generate value‐added products using simulated solar light, achieving 60–90% product selectivity and ≈70–130 µmol cm−2 h−1 product formation rates, which corresponds to 102–104 times higher activity than conventional photoreforming systems. The single‐light absorber device offers versatility in terms of substrate scope, sustaining unassisted photocurrents of 4–9 mA cm−2 for plastic, biomass, and glycerol conversion, in either a two‐compartment or integrated “artificial leaf” configuration. These configurations enable an effective reforming of non‐transparent waste streams and facile device retrieval from the reaction mixture. Accordingly, the presented PEC platform provides a proof‐of‐concept alternative towards photoreforming, approaching more closely the performance and versatility required for commercially viable waste utilization.

Ventilation plays a noteworthy role in maintaining a healthy, comfortable and energy-efficient indoor environment and mitigating the risk of aerosol transmission and disease infection (e.g., SARS-COV-2). In most commercial and office buildings, demand-controlled ventilation (DCV) systems are widely utilized to conserve energy based on occupancy. However, as the presence of occupants is often inherently stochastic, accurate occupancy prediction is challenging. This study, therefore, proposes an autoencoder Bayesian Long Short-term Memory neural network (LSTM) model for probabilistic occupancy prediction, taking account of model misspecification, epistemic uncertainty, and aleatoric uncertainty. Performances of the proposed models are evaluated using real data in an educational building at the University of Cambridge, UK. The models trained on data of one open-plan space are used to predict occupant numbers for other spaces (with similar layout and function) in the same building. The probabilistic occupant profiles are then used for estimating optimal ventilation rates for two scenarios (i.e., normal DCV mode for energy conservation and anti-infection mode for virus transmission prevention). Results show that, during the test period, for the 1-h ahead prediction, the proposed model achieved better performance with up to 5.8% mean absolute percentage error reduction than the traditional LSTM model. More flexible alternatives for ventilation can be offered by the proposed risk-aware decision-making schemes serving different purposes under real operation. The findings from this study provide new occupancy forecasting solutions and explore the potential of probabilistic decision making for building ventilation optimization.

Achieving reductions in global anthropogenic emissions necessary to mitigate the worst effects of climate change will require significant reductions in energy demand. However, there are concerns that energy demand reductions involving lifestyle and behavioural changes might negatively impact peoples’ wellbeing. The work in this thesis studies the impacts of how people spend their time – commonly known as time-use – to try to understand whether this is the true, or whether energy demand could be reduced while improving wellbeing. Using the UK as a case study, this issue is examined by determining the energy use and wellbeing attributes of different activities and lifestyles, by modelling the impacts of shifts in time-use between activities, and by comparing the importance of three specific changes that might impact future energy use and wellbeing. Firstly, based upon existing literature it is identified that there is a need to better understand the combined energy and wellbeing impacts of different activities and lifestyles. Combining UK time-use and energy consumption data, the energy intensity, enjoyment and sociability of time is studied. Comparing these metrics for different activities suggests that since the most enjoyable (and in some cases sociable) activities are generally the least energy-intensive, acceptable (or popular) lifestyle changes might exist that reduce national energy use and improve wellbeing. However, studying changes between 2000 and 2015 shows that while the population’s time became less energy-intensive, there was little change in average enjoyment and a reduction in sociability. Segmenting the population by age reveals that an ageing population could present a challenge since energy use broadly increases with age-group while social contact reduces. However, comparing occupations highlights opportunities for specific actions that could improve wellbeing and reduce energy use, while regional differences suggest that wellbeing might be improved without increasing energy use. Having determined the energy intensity and wellbeing associated with different uses of time, the impacts of possible time-use changes are then studied. Acknowledging the difficulty in trying to predict how people might choose to re-allocate time in different situations, a sensitivity-based approach is used to study the impacts of a wide range of possible shifts in time between activities. The approach is then applied to explore the impacts of extreme lifestyle changes associated with COVID-19 lockdown measures in the UK and validated against real-world observations during the pandemic. While activity changes associated with lockdown measures reduce energy use, there are varying implications for peoples’ wellbeing, with the youngest appearing to be most negatively impacted but those able to work from home potentially benefiting. Although lockdown measures prevented some of the most enjoyable and sociable activities from happening, alternative activity changes could be supported in future that reduce energy use while improving wellbeing. Finally, time is used as a basis to compare the importance of different types of changes and help to prioritise actions. This is demonstrated by studying the combined impacts of three example changes – greater home working, changes in commuting transport modes and car intensity – on office workers’ energy use and wellbeing. The results show that working from home could have a greater impact upon office workers’ average energy use and enjoyment than changes to commuting modes, but that the social contact provided by the office could be difficult to replace. The study also demonstrates different ways that energy savings might be achieved through home working, shifts in commuting modes and changes to vehicle intensity. This approach could be used more widely to compare a broader range of changes, understand their interactions and different ways to achieve outcomes, and help to identify those changes that are most important to reduce energy use and improve wellbeing. The work presented in this thesis shows that time-use can be used as a basis to examine energy demand and wellbeing together. Using time-use to link these issues enables trade-offs or co-benefits due to different uses of time to be determined and allows rebound effects to be considered. The results suggest that reducing energy use can be achieved at the same time as improving wellbeing. The hope is that the approaches and findings presented in this thesis can provide a basis for wider discussion and a platform for future work to support climate change mitigation strategies that are positive for both the environment and society.

AbstractThere is increasing concern that climate change poses an existential risk to humanity. Understanding these worst-case scenarios is essential for good risk management. However, our knowledge of the causal pathways through which climate change could cause societal collapse is underdeveloped. This paper aims to identify and structure an empirical evidence base of the climate change, food insecurity and societal collapse pathway. We first review the societal collapse and existential risk literature and define a set of determinants of societal collapse. We develop an original methodology, using these determinants as societal collapse proxies, to identify an empirical evidence base of climate change, food insecurity and societal collapse in contemporary society and then structure it using a novel-format causal loop diagram (CLD) defined at global scale and national granularity. The resulting evidence base varies in temporal and spatial distribution of study and in the type of data-driven methods used. The resulting CLD documents the spread of the evidence base, using line thickness and colour to depict density and type of data-driven method respectively. It enables exploration of how the effects of climate change may undermine agricultural systems and disrupt food supply, which can lead to economic shocks, socio-political instability as well as starvation, migration and conflict. Suggestions are made for future work that could build on this paper to further develop our qualitative understanding of, and quantitative complex systems modelling capabilities for analysing, the causal pathways between climate change and societal collapse.

Universal access to clean electricity (SDG7) in remote areas of the rural South remains a key challenge for economic growth, and has particular implications for equitable, inclusive and sustainable development. In Pakistan, techno-economic constraints in grid expansion for last-mile users, combined with the country’s high solar energy potential make off-grid solar energy generation a viable solution, provided its technological, social and economic implications are well-understood in terms of actual energy demands and designed for equitable distribution. This paper presents a socio-technical feasibility assessment for designing equitable and inclusive off-grid solar systems using the case-study of Helario village in Tharparkar, Pakistan, with a key focus on gender-specific benefits. A mixed-methods approach is used to conduct a baseline field assessment of existing energy sources, community needs, women’s access and energy use, affordability, future energy aspirations and social acceptability of renewable energy technologies. Results indicate gendered differences in mobility, education, everyday practices and income that have socio-economic implications, whereby women can benefit more from electrification, particularly when electricity is interlinked with access to clean water. Results are used to model, simulate and optimise a solar-battery mini-grid system for tiered and equitable energy access using CLOVER. Analysis shows that a system designed with a 10-year lifetime provides the lowest levelised cost of electricity and minimum emissions intensity, emphasising the need for long-term energy system planning. This paper serves as a demonstration for policymakers, project developers and rural communities for designing more equitable and inclusive energy systems with clear gendered implications for sustainable future access.