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Reliable access to clean and affordable water is prerequisite for human well being, but its provision in cities generates environmental externalities including greenhouse gas (GHG) emissions. As policy-makers target opportunities to mitigate GHGs in line with the Paris Agreement, it remains vague how urban water management can contribute to the goal of limiting climate warming to 1.5 °C. This perspective guides policy-makers in the selection of innovative technologies and strategies for leveraging urban water management as a climate change mitigation solution. Recent literature, data and scenarios are reviewed to shine a light on the GHG mitigation potential and the key areas requiring future research. Increasing urban water demands in emerging economies and over-consumption in developed regions pose mitigation challenges due to energy and material requirements that can be partly offset through end-use water conservation and expansion of decentralized, nature-based solutions. Policies that integrate urban water and energy flows, or reconfigure urban water allocation at the river basin-level remain untapped mitigation solutions with large gaps in our understanding of potentials.

Fog computing is a new paradigm that extends the Cloud platform model by providing computing resources on the edges of a network. It can be described as a cloud-like platform having similar data, computation, storage and application services, but is fundamentally different in that it is decentralized. In addition, Fog systems are capable of processing large amounts of data locally, operate on-premise, are fully portable, and can be installed on heterogeneous hardware. These features make the Fog platform highly suitable for time and location-sensitive applications. For example, Internet of Things (IoT) devices are required to quickly process a large amount of data. This wide range of functionality driven applications intensifies many security issues regarding data, virtualization, segregation, network, malware and monitoring. This paper surveys existing literature on Fog computing applications to identify common security gaps. Similar technologies like Edge computing, Cloudlets and Micro-data centres have also been included to provide a holistic review process. The majority of Fog applications are motivated by the desire for functionality and end-user requirements, while the security aspects are often ignored or considered as an afterthought. This paper also determines the impact of those security issues and possible solutions, providing future security-relevant directions to those responsible for designing, developing, and maintaining Fog systems.

Seasonal mismatches between electricity supply and demand is increasing due to expanded use of wind, solar and hydropower resources, which in turn raises the interest on low-cost seasonal energy storage options. Seasonal pumped hydropower storage (SPHS) can provide long-term energy storage at a relatively low-cost and co-benefits in the form of freshwater storage capacity. We present the first estimate of the global assessment of SPHS potential, using a novel plant-siting methodology based on high-resolution topographical and hydrological data. Here we show that SPHS costs vary from 0.007 to 0.2 US$ m −1 of water stored, 1.8 to 50 US$ MWh −1 of energy stored and 370 to 600 US$ kW −1 of installed power generation. This potential is unevenly distributed with mountainous regions demonstrating significantly more potential. The estimated world energy storage capacity below a cost of 50 US$ MWh −1 is 17.3 PWh, approximately 79% of the world electricity consumption in 2017. The potential of seasonal pumped hydropower storage (SPHS) plant to fulfil future energy storage requirements is vast in mountainous regions. Here the authors show that SPHS costs vary from 0.007 to 0.2 US$ m −3 of water stored, 1.8 to 50 US$ MWh −1 of energy stored and 0.37 to 0.6 US$ GW −1 of installed power generation capacity.

The United Nations' Sustainable Development Goals (SDGs) provide guide-posts to society as it attempts to respond to an array of pressing challenges. One of these challenges is energy; thus, the SDGs have become paramount for energy policy-making. Yet, while governments throughout the world have already declared the SDGs to be 'integrated and indivisible', there are still knowledge gaps surrounding how the interactions between the energy SDG targets and those of the non-energy-focused SDGs might play out in different contexts. In this review, we report on a large-scale assessment of the relevant energy literature, which we conducted to better our understanding of key energy-related interactions between SDGs, as well as their context-dependencies (relating to time, geography, governance, technology, and directionality). By (i) evaluating the nature and strength of the interactions identified, (ii) indicating the robustness of the evidence base, the agreement of that evidence, and our confidence in it, and (iii) highlighting critical areas where better understanding is needed or context dependencies should be considered, our review points to potential ways forward for both the policy making and scientific communities. First, we find that positive interactions between the SDGs outweigh the negative ones, both in number and magnitude. Second, of relevance for the scientific community, in order to fill knowledge gaps in critical areas, there is an urgent need for interdisciplinary research geared toward developing new data, scientific tools, and fresh perspectives. Third, of relevance for policy-making, wider efforts to promote policy coherence and integrated assessments are required to address potential policy spillovers across sectors, sustainability domains, and geographic and temporal boundaries. The task of conducting comprehensive science-to-policy assessments covering all SDGs, such as for the UN's Global Sustainable Development Report, remains manageable pending the availability of systematic reviews focusing on a limited number of SDG dimensions in each case.

Hydro-climatic extremes can affect the reliability of electricity supply, in particular in countries that depend greatly on hydropower or cooling water and have a limited adaptive capacity. Assessments of the vulnerability of the power sector and of the impact of extreme events are thus crucial for decision-makers, and yet often they are severely constrained by data scarcity. Here, we introduce and validate an energy-climate-water framework linking remotely-sensed data from multiple satellite missions and instruments (TOPEX/POSEIDON. OSTM/Jason, VIIRS, MODIS, TMPA, AMSR-E) and field observations. The platform exploits random forests regression algorithms to mitigate data scarcity and predict river discharge variability when ungauged. The validated predictions are used to assess the impact of hydroclimatic extremes on hydropower reliability and on the final use of electricity in urban areas proxied by nighttime light radiance variation. We apply the framework to the case of Malawi for the periods 2000-2018 and 2012-2018 for hydrology and power, respectively. Our results highlight the significant impact of hydro-climatic variability and dry extremes on both the supply of electricity and its final use. We thus show that a modelling framework based on open-access data from satellites, machine learning algorithms, and regression analysis can mitigate data scarcity and improve the understanding of vulnerabilities. The proposed approach can support long-term infrastructure development monitoring and identify vulnerable populations, in particular under a changing climate.

Understanding the interplay between multiple climate change risks and socioeconomic development is increasingly required to inform effective actions to manage these risks and pursue sustainable development. We calculate a set of 14 impact indicators at different levels of global mean temperature (GMT) change and socioeconomic development covering water, energy and land sectors from an ensemble of global climate, integrated assessment and impact models. The analysis includes changes in drought intensity and water stress index, cooling demand change and heat event exposure, habitat degradation and crop yield, amongst others. To investigate exposure to multi-sector climate impacts, these are combined with gridded socioeconomic projections of population and those 'vulnerable to poverty' from three Shared Socioeconomic Pathways (SSP) (income <$10/day, currently 4.2 billion people). We show that global exposure to multi-sector risks approximately doubles between 1.5 °C and 2 °C GMT change, doubles again with 3 °C GMT change and is ~6x between the best and worst cases (SSP1/1.5 °C vs SSP3/3 °C, 0.8-4.7bi). For populations vulnerable to poverty, the exposure is an order of magnitude greater (8-32x) in the high poverty and inequality scenarios (SSP3) compared to sustainable socioeconomic development (SSP1). Whilst 85%-95% of global exposure falls to Asian and African regions, they have 91%-98% of the exposed and vulnerable population (depending on SSP/GMT combination), approximately half of which in South Asia. In higher warming scenarios, African regions have growing proportion of the global exposed and vulnerable population, ranging from 7%-17% at 1.5 °C, doubling to 14%-30% at 2 °C and again to 27%-51% at 3 °C. Finally, beyond 2 °C and at higher risk thresholds, the world's poorest are disproportionately impacted, particularly in cases (SSP3) of high inequality in Africa and southern Asia. Sustainable development that reduces poverty, mitigates emissions and meets targets in the water, energy and land sectors has the potential for order-of-magnitude scale reductions in multi-sector climate risk for the most vulnerable.

An electricity generation planning framework incorporating adaptation to hydro-climatic change is presented. The planning framework internalizes risks and opportunities associated with alternative hydro-climate scenarios to identify a long-term system configuration robust to uncertainty. The implications of a robust response to hydro-climatic change are demonstrated for the electricity system in British Columbia (BC), Canada. Adaptation strategy is crucial in this region, mainly due to the large contribution of hydropower resources to regional electricity supply. Analysis of results from basin-scale hydrologic models driven with downscaled global climate data suggest that shifts in regional streamflow characteristics by the year 2050 are likely to increase BC’s annual hydropower potential by more than 10 %. These effects combined with an estimated decrease in electricity demand by 2 % due to warmer temperatures, could provide an additional 11 TWh of annual energy. Uncertainties in these projected climate impacts indicate technology configurations offering significant long-term operational flexibility will be needed to ensure system reliability. Results from the regional long-term electricity generation model incorporating adaptive capacity show the significant shifts required in the non-hydro capacity mix to ensure system robustness cause an increase in cumulative operating costs of between 1 and 7 %. Analysis of technology configurations involving high-penetrations of wind generation highlights interactions between flexibility requirements occurring over multiple temporal scales.

Analysing access control policies is an essential process for ensuring over-prescribed permissions are identified and removed. This is a time-consuming and knowledge-intensive process, largely because there is a wealth of policy information that needs to be manually examined. Furthermore, there is no standard definition of what constitutes an over-entitled permission within an organisation’s access control policy, making it not possible to develop automated rule-based approaches. It is often the case that over-entitled permissions are subjective to an organisation’s role-based structure, where access is be divided and managed based on different employee needs. In this context, an irregular permission could be one where an employee has frequently changed roles, thus accumulating a wide-ranging set of permissions. There is no one size fits all approach to identifying permissions where an employee is receiving more permission than is necessary, and it is necessary to examine them in the context of the organisation to establish their individual risk . Risk is not a binary measure and, in this work, an approach is built using Fuzzy Logic to determine an overall risk rating, which can then be used to make a more informed decision as to whether a user is over-entitled and presenting risk to the organisation. This requires the exploratory use of establishing resource sensitivity and user trust as measures to determine a risk rating. The paper presents a generic solution, which has been implemented to perform experimental analysis on Microsoft’s New Technology File System to show how this works in practice. A simulation using expert knowledge for comparison is then performed to demonstrate how effective it is at helping the user identify potential irregular permissions.

Quantifying water implications of energy transitions is important for assessing long-term freshwater sustainability since large volumes of water are currently used throughout the energy sector. In this paper, we assess direct global energy sector water use and thermal water pollution across a broad range of energy system transformation pathways to assess water impacts of a 2 °C climate policy. A global integrated assessment model is equipped with the capabilities to account for the water impacts of technologies located throughout the energy supply chain. The model framework is applied across a broad range of 2 °C scenarios to highlight long-term water impact uncertainties over the 21st century. We find that water implications vary significantly across scenarios, and that adaptation in power plant cooling technology can considerably reduce global freshwater withdrawals and thermal pollution. Global freshwater consumption increases across all of the investigated 2 °C scenarios as a result of rapidly expanding electricity demand in developing regions and the prevalence of freshwater-cooled thermal power generation. Reducing energy demand emerges as a robust strategy for water conservation, and enables increased technological flexibility on the supply side to fulfill ambitious climate objectives. The results underscore the importance of an integrated approach when developing water, energy, and climate policy, especially in regions where rapid growth in both energy and water demands is anticipated.

Low-carbon investments are necessary for driving the energy system transformation that is called for by both the Paris Agreement and Sustainable Development Goals. Improving understanding of the scale and nature of these investments under diverging technology and policy futures is therefore of great importance to decision makers. Here, using six global modelling frameworks, we show that the pronounced reallocation of the investment portfolio required to transform the energy system will not be initiated by the current suite of countries’ Nationally Determined Contributions. Charting a course toward ‘well below 2 °C’ instead sees low-carbon investments overtaking fossil investments globally by around 2025 or before and growing thereafter. Pursuing the 1.5 °C target demands a marked upscaling in low-carbon capital beyond that of a 2 °C-consistent future. Actions consistent with an energy transformation would increase the costs of achieving the goals of energy access and food security, but reduce the costs of achieving air-quality goals. The scale and nature of energy investments under diverging technology and policy futures is of great importance to decision makers. Here, a multi-model study projects investment needs under countries’ nationally determined contributions and in pathways consistent with achieving the 2 °C and 1.5 °C targets as well as certain SDGs.