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The New Zealand Government has a goal of a 100% renewable electricity system by 2035. Wind generation is expected to play a major role in achieving this target. However, there is limited public data on current and potential wind generation. We use the Renewables.ninja model to simulate wind output at 44 wind farm sites in New Zealand over a 20-year period. We make our data publicly available and use them to analyse New Zealand's wind resources. We find the long-run average capacity factors over all current and potential sites is 40%. It is lowest in autumn (around 35%) and highest in spring (around 45%). Output is similar across all demand percentiles with little correlation between wind output and demand. A small positive correlation exists between wind output and daily inflows into hydro storage dams. A more significant positive correlation exists between wind output and inflows in the period leading up to winter (when lake levels are typically lowest), implying that wind cannot help energy shortfall during dry years. Finally, we explore how much wind capacity must be installed to give a 100% renewable electricity system, and the trade-offs between energy storage and spilling wind for achieving this target. • First open simulation of wind power in New Zealand's electricity market. • The current and proposed future wind fleets have long-run capacity factors of 40 ± 2%. • On average, wind provides an equal contribution at times of high and low demand. • Wind has a positive correlation with hydro inflows, implying no help against dry years. • 100% renewable electricity is viable with the proposed wind farms and 7-day storage. [ABSTRACT FROM AUTHOR]

• Fleet turnover model created for the UK up to 2050. • Vehicle and power station air pollutant and CO 2eq emissions calculated. • BEVs reduce CO 2eq and NO x emissions but leave non-exhaust PM 2.5 unmitigated. • BEV uptake rates impact cumulative CO 2eq emissions, but not air pollutants. • Reducing vehicle kilometres can mitigate non-exhaust PM 2.5 emissions. The rapid uptake of new vehicle technologies will change the environmental impact of road transport. The emissions produced in power plants supplying electric vehicles (EVs) and vehicular non-exhaust PM 2.5 emissions leaves the benefits of EVs unclear. We develop a fleet turnover model to assess how different vehicle technologies, the rate of technological change, and changing transport demand impact vehicle and power station CO 2eq and air pollutant emissions. By 2050, the transition to EVs reduces yearly CO 2eq emissions by 98% and cumulative CO 2eq emissions by over 50%; accelerating or delaying EV uptake by 5 years changes these results by 1% and 17%, respectively. By 2050, EVs reduce annual NO x emissions by 97%, but have little impact on PM 2.5 due to vehicular non-exhaust emissions. Accelerating or delaying EV uptake had little impact on air pollution emissions. Reducing vehicle kilometres has the potential to reduce non-exhaust PM 2.5 emissions by 20% in the long-term. [ABSTRACT FROM AUTHOR]

Abstract Several influential energy systems models (ESMs) indicate that renewable energy must supply a large share of the world's electricity to limit global temperature increases to 1.5 °C. To better represent the costs and other implications of such a transition, it is important that ESMs can realistically characterise the technical and economic potential of renewable energy resources. This paper presents a Geospatial Information System methodology for estimating the global offshore wind energy potential, i.e. the terawatt hour per year (TWh/yr) production potential of wind farms, assuming capacity could be built across the viable offshore area of each country. A bottom-up approach characterises the capacity factors of offshore wind farms by estimating the available wind power from high resolution global wind speed data sets. Temporal phenomena are retained by binning hourly wind speeds into 32 time slices per year considering the wind resource across several decades. For 157 countries with a viable offshore wind potential, electricity generation potential is produced in tranches according to the distance to grid connection, water depth and average annual capacity factor. These data can be used as inputs to ESMs and to assess the economically viable offshore wind energy potential, on a global or per-country basis. Highlights • Offshore wind energy potentials according to distance to the coast and water depth. • Generation potential is time-explicit to be used in energy system models. • Capacity potential depends on local capacity factors, water depth and available area. • 329,600 Terawatt hours per year of offshore wind energy is feasible, globally. [ABSTRACT FROM AUTHOR]

Britain and Germany saw unprecedented growth of variable renewable energy (VRE) in the last decade. Many studies suggest this will significantly raise short-term power system operation costs for balancing and congestion management. We review the actual development of these costs, their allocation and policy implications in both countries. Since 2010, system operation costs have increased by 62% in Britain (with a five-fold increase in VRE capacity) and remained comparable in Germany (with capacity doubling). Within this, balancing costs stayed level in Britain (–4%) and decreased substantially in Germany (–72%), whilst congestion management costs have grown 74% in Britain and 14-fold in Germany. Curtailment costs vary widely from year to year, and should fall strongly when ongoing and planned grid upgrades are completed. Curtailment rates for wind farms have risen to 4–5% in Germany and 5–6% in Britain (0–1% for offshore and 15–16% for onshore Scottish farms). Policy debates regarding the balancing system are similar in both countries, focussing on strengthening imbalance price signals and the extent that VRE generators bear the integration costs they cause. Both countries can learn from each other's balancing market and imbalance settlement designs. Britain should reform its balancing markets to be more transparent, competitive and open to new providers (especially VRE generators). Shorter trading intervals and gate closure would both require and enable market participants (including VRE) to take more responsibility for balancing. Germany should consider a reserve energy market and move to marginal imbalance pricing. [ABSTRACT FROM AUTHOR]

Wind and solar power have experienced rapid cost declines and are being deployed at scale. However, their output variability remains a key problem for managing electricity systems, and the implications of multi-day to multi-year variability are still poorly understood. As other energy-using sectors are electrified, the shape and variability of electricity demand will also change. We develop an open framework for quantifying the impacts of weather on electricity supply and demand using the Renewables.ninja and DESSTINEE models. We demonstrate this using a case study of Britain using National Grid's Two Degrees scenario forwards to 2030. We find the British electricity system is rapidly moving into unprecedented territory, with peak demand rising above 70 GW due to electric heating, and intermittent renewable output exceeding demand as early as 2021. Hourly ramp-rates widen by 50% and year-to-year variability increases by 80%, showing why future power system studies must consider multiple years of data, and the influence of weather on both supply and demand. Our framework is globally applicable, and allows detailed scenarios of hourly electricity supply and demand to be explored using only limited input data such as annual quantities from government scenarios or broader energy systems models. [ABSTRACT FROM AUTHOR]

A new approach is required to determine a technology's value to the power systems of the 21st century. Conventional cost-based metrics are incapable of accounting for the indirect system costs associated with intermittent electricity generation, in addition to environmental and security constraints. In this work, we formalise a new concept for power generation and storage technology valuation which explicitly accounts for system conditions, integration challenges, and the level of technology penetration. The centrepiece of the system value (SV) concept is a whole electricity systems model on a national scale, which simultaneously determines the ideal power system design and unit-wise operational strategy. It brings typical Process Systems Engineering thinking into the analysis of power systems. The model formulation is a mixed-integer linear optimisation and can be understood as hybrid between a generation expansion and a unit commitment model. We present an analysis of the future UK electricity system and investigate the SV of carbon capture and storage equipped power plants (CCS), onshore wind power plants, and grid-level energy storage capacity. We show how the availability of different low-carbon technologies impact the optimal capacity mix and generation patterns. We find that the SV in the year 2035 of grid-level energy storage is an order of magnitude greater than that of CCS and wind power plants. However, CCS and wind capacity provide a more consistent value to the system as their level of deployment increases. Ultimately, the incremental system value of a power technology is a function of the prevalent system design and constraints. [ABSTRACT FROM AUTHOR]

Several influential energy systems models indicate that renewable energy must provide a significant share of the world's electricity to limit global temperature rises to below 2 °C this century. To better represent the costs and other implications of this shift, it is important that these models realistically characterise the technical and economic potential of renewable energy technologies. Towards this goal, this paper presents the first temporally-explicit Geospatial Information System (GIS) methodology to characterise the global onshore wind energy potential with respect to topographical features, land use and environmental constraints. The approach combines the hourly NASA MERRA-2 global wind speed data set with the spatially-resolved DTU Global Wind Atlas. This yields high resolution global capacity factors for onshore wind, binned into seasonal and diurnal time-slices to capture the important temporal variability. For each country, the wind power generation capacity available for various capacity factor ranges is produced, and made freely available to the community. This data set can be used to assess the economically viable wind energy potential on a global or per-country basis, and as an input to various energy systems models. [ABSTRACT FROM AUTHOR]

Society's dependence on weather systems has broadened to include electricity generation from wind turbines. Climate change is altering energy flows in the atmosphere, which will affect the economic potential of wind power. Changes to wind resources and their upstream impacts on the energy industry have received limited academic attention, despite their risks earning interest from investors. We propose a framework for assessing the impact of climate change on the cost of wind energy, going from the change in hourly wind speed distributions from radiative forcing through to energy output and levelised cost of electricity (LCOE) from wind farms. The paper outlines the proof of concept for this framework, exploring the limitations of global climate models for assessing wind resources, and a novel Weibull transfer function to characterise the climate signal. The framework is demonstrated by considering the UK's wind resources to 2100. Results are mixed: capacity factors increase in some regions and decrease in others, while the year-to-year variation generally increases. This highlights important financial and risk impacts which can be adopted into policy to enhance energy system resilience to the impacts of climate change. We call for greater emphasis to be placed on modelling wind resources in climate science. [ABSTRACT FROM AUTHOR]

Solar PV is rapidly growing globally, creating difficult questions around how to efficiently integrate it into national electricity grids. Its time-varying power output is difficult to model credibly because it depends on complex and variable weather systems, leading to difficulty in understanding its potential and limitations. We demonstrate how the MERRA and MERRA-2 global meteorological reanalyses as well as the Meteosat-based CM-SAF SARAH satellite dataset can be used to produce hourly PV simulations across Europe. To validate these simulations, we gather metered time series from more than 1000 PV systems as well as national aggregate output reported by transmission network operators. We find slightly better accuracy from satellite data, but greater stability from reanalysis data. We correct for systematic bias by matching our simulations to the mean bias in modeling individual sites, then examine the long-term patterns, variability and correlation with power demand across Europe, using thirty years of simulated outputs. The results quantify how the increasing deployment of PV substantially changes net power demand and affects system adequacy and ramping requirements, with heterogeneous impacts across different European countries. The simulation code and the hourly simulations for all European countries are available freely via an interactive web platform, www.renewables.ninja . [ABSTRACT FROM AUTHOR]

Reanalysis models are rapidly gaining popularity for simulating wind power output due to their convenience and global coverage. However, they should only be relied upon once thoroughly proven. This paper reports the first international validation of reanalysis for wind energy, testing NASA's MERRA and MERRA-2 in 23 European countries. Both reanalyses suffer significant spatial bias, overestimating wind output by 50% in northwest Europe and underestimating by 30% in the Mediterranean. We derive national correction factors, and show that after calibration national hourly output can be modelled with R 2 above 0.95. Our underlying data are made freely available to aid future research. We then assess Europe's wind resources with twenty-year simulations of the current and potential future fleets. Europe's current average capacity factor is 24.2%, with countries ranging from 19.5% (Germany) to 32.4% (Britain). Capacity factors are rising due to improving technology and locations; for example, Britain's wind fleet is now 23% more productive than in 2005. Based on the current planning pipeline, we estimate Europe's average capacity factor could increase by nearly a third to 31.3%. Countries with large stakes in the North Sea will see significant gains, with Britain's average capacity factor rising to 39.4% and Germany's to 29.1%. [ABSTRACT FROM AUTHOR]

This paper presents the optimal design and operation of integrated wind-hydrogen-electricity networks using the general mixed integer linear programming energy network model, STeMES (Samsatli and Samsatli, 2015). The network comprises: wind turbines; electrolysers, fuel cells, compressors and expanders; pressurised vessels and underground storage for hydrogen storage; hydrogen pipelines and electricity overhead/underground transmission lines; and fuelling stations and distribution pipelines. The spatial distribution and temporal variability of energy demands and wind availability were considered in detail in the model. The suitable sites for wind turbines were identified using GIS, by applying a total of 10 technical and environmental constraints (buffer distances from urban areas, rivers, roads, airports, woodland and so on), and used to determine the maximum number of new wind turbines that can be installed in each zone. The objective is the minimisation of the total cost of the network, subject to satisfying all of the demands of the domestic transport sector in Great Britain. The model simultaneously determines the optimal number, size and location of each technology, whether to transmit the energy as electricity or hydrogen, the structure of the transmission network, the hourly operation of each technology and so on. The cost of distribution was estimated from the number of fuelling stations and length of the distribution pipelines, which were determined from the demand density at the 1 km level. Results indicate that all of Britain's domestic transport demand can be met by on-shore wind through appropriately designed and operated hydrogen-electricity networks. Within the set of technologies considered, the optimal solution is: to build a hydrogen pipeline network in the south of England and Wales; to supply the Midlands and Greater London with hydrogen from the pipeline network alone; to use Humbly Grove underground storage for seasonal storage and pressurised vessels at different locations for hourly balancing as well as seasonal storage; for Northern Wales, Northern England and Scotland to be self-sufficient, generating and storing all of the hydrogen locally. These results may change with the inclusion of more technologies, such as electricity storage and electric vehicles. [ABSTRACT FROM AUTHOR]

The merit order stack is used to tackle a wide variety of problems involving electricity dispatch. The simplification it relies on is to neglect dynamic issues such as the cost of starting stations. This leads the merit order stack to give a poor representation of the hourly pattern of prices and under-estimate the optimal level of investment in both peaking and inflexible baseload generators, and thus their run-times by up to 30%. We describe a simple method for incorporating start-up costs using a single equation derived from the load curve and station costs. The technique is demonstrated on the British electricity system in 2010 to test its performance against actual outturn, and in a 2020 scenario with increased wind capacity where it is compared to a dynamic unit-commitment scheduler. Our modification yields a better representation of electricity prices and reduces the errors in capacity investment by a factor of two. [ABSTRACT FROM AUTHOR]

The Republic of South Africa (RSA), often seen as the “Powerhouse of Africa” is facing major energy challenges. (Un)planned outages, energy shortages, blackouts, high energy tariffs, many years of underinvestment in power infrastructure and energy poverty in low income households are the main issues. To eradicate this, the RSA government has rolled out several energy and energy efficiency programmes and initiatives with a strong emphasis on off-grid Renewable Energy solutions, Hydrogen Energy, and oil and gas (including shale) exploration opportunities. Since 2013, most of the country's top construction projects focussed on Renewable Energy projects. The country's aspiration is to build-up to an “industrial revolution” incorporating the development of a “Green Economy” which could significantly boost the nation manufacturing base. The aim of this paper is to provide a fact based analysis of the current energy landscape in RSA. This can then be used alongside the aspirations and grand challenges the country has identified to ascertain the scale of the issues that the country faces. This paper is not set out to “solve” the problems of today's energy in RSA, but to provide the evidence needed to think more systematically about them. [ABSTRACT FROM AUTHOR]

Combined Heat and Power (CHP) is the sequential or simultaneous generation of multiple forms of useful energy, usually electrical and thermal, in a single and integrated system. Implementing CHP systems in the current energy sector may solve energy shortages, climate change and energy conservation issues. This review paper is divided into six sections: the first part defines and classifies the types of fuel cell used in CHP systems; the second part discusses the current status of fuel cell CHP (FC-CHP) around the world and highlights the benefits and drawbacks of CHP systems; the third part focuses on techniques for modelling CHP systems. The fourth section gives a thorough comparison and discussion of the two main fuel cell technologies used in FC-CHP (PEMFC and SOFC), characterising their technical performance and recent developments from the major manufacturers. The fifth section describes all the main components of FC-CHP systems and explains the issues connected with their practical application. The last part summarises the above, and reflects on micro FC-CHP system technology and its future prospects. [ABSTRACT FROM AUTHOR]

Fuel cells are a promising technology for combined heat and power (CHP); however their efficiency and carbon benefits are often overlooked because of their reliance on fossil fuels. This paper sets out the numerical methods and evidence of real-world performance needed to compare fuel cells with other low-carbon technologies. It is demonstrated that firstly, the efficiency of present-day fuel cells is high enough to outperform the best electric heat pumps, even when these are powered exclusively by the best modern power stations. The equivalent COP (coefficient of performance) of today’s fuel cells ranges from 5 to ∞, compared to 3–4 for the best ground source heat pumps. Secondly, this high efficiency means that even when fuelled with natural gas, the heat from a fuel cell is zero- or even negative-carbon when electricity from central power stations is displaced. [ABSTRACT FROM AUTHOR]

The debate on low-carbon heat in Europe has become focused on a narrow range of technological options and has largely neglected hydrogen and fuel cell technologies, despite these receiving strong support towards commercialisation in Asia. This review examines the potential benefits of these technologies across different markets, particularly the current state of development and performance of fuel cell micro-CHP. Fuel cells offer some important benefits over other low-carbon heating technologies, and steady cost reductions through innovation are bringing fuel cells close to commercialisation in several countries. Moreover, fuel cells offer wider energy system benefits for high-latitude countries with peak electricity demands in winter. Hydrogen is a zero-carbon alternative to natural gas, which could be particularly valuable for those countries with extensive natural gas distribution networks, but many national energy system models examine neither hydrogen nor fuel cells for heating. There is a need to include hydrogen and fuel cell heating technologies in future scenario analyses, and for policymakers to take into account the full value of the potential contribution of hydrogen and fuel cells to low-carbon energy systems. [ABSTRACT FROM AUTHOR]

Abstract: Ageing is a fact of life. Just as with conventional forms of power generation, the energy produced by a wind farm gradually decreases over its lifetime, perhaps due to falling availability, aerodynamic performance or conversion efficiency. Understanding these factors is however complicated by the highly variable availability of the wind. This paper reveals the rate of ageing of a national fleet of wind turbines using free public data for the actual and theoretical ideal load factors from the UK's 282 wind farms. Actual load factors are recorded monthly for the period of 2002–2012, covering 1686 farm-years of operation. Ideal load factors are derived from a high resolution wind resource assessment made using NASA data to estimate the hourly wind speed at the location and hub height of each wind farm, accounting for the particular models of turbine installed. By accounting for individual site conditions we confirm that load factors do decline with age, at a similar rate to other rotating machinery. Wind turbines are found to lose 1.6 ± 0.2% of their output per year, with average load factors declining from 28.5% when new to 21% at age 19. This trend is consistent for different generations of turbine design and individual wind farms. This level of degradation reduces a wind farm's output by 12% over a twenty year lifetime, increasing the levelised cost of electricity by 9%. [Copyright &y& Elsevier]

We use a k-means clustering algorithm to partition national electricity demand data for Great Britain and apply a novel profiling method to obtain a set of representative demand profiles for each year over the period 1994–2005. We then use a simulated dispatch model to assess the accuracy of these daily profiles against the complete dataset on a year-to-year basis. We find that the use of data partitioning does not compromise the accuracy of the simulations for most of the main variables considered, even when simulating significant intermittent wind generation. This technique yields 50-fold gains in terms of computational speed, allowing complex Monte Carlo simulations and sensitivity analyses to be performed with modest computing resource. [ABSTRACT FROM PUBLISHER]

Abstract: Numerous academic and industrial estimates place the cost of future mass-produced small stationary fuel cell systems at around $1000 per kW, which compares well with targets set by agencies such as the US Department of Energy. Actual sale prices do not fit so neatly with these targets, and are currently 25–50 times higher even though mass production began three years ago. This paper explores the void between academic projections and commercial reality. It presents a systematic review of cost data from manufacturers in Europe, Asia and the US, along with near-term projections from manufacturers and other relevant organisations. Using these data, the potential for cost reductions through industry scale-up and learning by doing are quantified. The minimum feasible price of a typical 1 kW natural gas combined heat and power system is then estimated from industry data. Based on the findings, even a heroic effort by industry is unlikely to reduce the price of small domestic-scale systems to the $1000/kW mark. By aligning the scope and boundaries of cost estimates with the realities of domestic microgeneration systems, we show that a long-term target of $3000–5000 for 1–2 kW systems is more realistic, and could feasibly be attained by 2020 at the current rate of progress. [Copyright &y& Elsevier]

Abstract: Decarbonising transport is proving to be one of today''s major challenges for the global automotive industry due to many factors such as the increase in greenhouse gas and particulate emissions affecting not only the climate but also humans, the increase in pollution, rapid oil depletion, issues with energy security and dependency from foreign sources and population growth. For more than a century, our society has been dependent upon oil, and major breakthroughs in low- and ultra-low carbon technologies and vehicles are urgently required. This review paper highlights the current status of hybrid, battery and fuel cell electric vehicles from an electrochemical and market point of view. The review paper also discusses the advantages and disadvantages of using each technology in the automotive industry and the impact of these technologies on consumers. [Copyright &y& Elsevier]

Fossil fuel is the major source of energy for all forms of motor vehicle, with gasoline and diesel fuels dominating our personal transport. Although biofuels have been used to inject some renewable energy into the transport system, imports of oil and gas to Europe, the USA and Japan continue to rise. A move to reduce energy consumption and carbon emissions by driving more efficient vehicles is therefore necessary. This paper considers a shift to reduced friction hydrogen electric vehicles that give three major benefits: (i) sourcing hydrogen from low carbon sources like wind, biomass, nuclear and solar; (ii) using an electric drivetrain to minimize energy conversion to heat; and (iii) reducing resistances to motion to give lower energy requirements for traction. This energy dissipation due to friction proves to be a complex mixture of tyre losses, brake adhesion, wind resistance, fuel conversion inefficiency, motor resistance, drivetrain losses, auxiliary power consumption and so on. By considering the addition of many loss terms, it is shown that the energy dissipation in fuel cell-powered vehicles resolves into a linear function of vehicle weight. [ABSTRACT FROM AUTHOR]

Abstract: Fuel cells already provide heat and power to people’s homes with lower direct CO2 emissions and fuel consumption than traditional methods. However, their whole life cycle, including manufacture and disposal, must be considered to verify that these environmental impacts are actually reduced and not merely shifted elsewhere. The total carbon footprint and energy payback times have been widely reported for other emerging microgeneration technologies, but have not previously been calculated for fuel cell systems. This paper presents a life cycle assessment comparing solid oxide fuel cell (SOFC) based domestic CHP with the current embedded technologies in the UK. An inventory is given for the construction of a 1 kW stack and then its operation is simulated in detail using measured energy demands from hundreds of UK houses. Producing a 1 kW planar SOFC micro-CHP system was estimated to require 12–17 GJ of energy input and emit 700–950 kg of CO2, although these impacts triple when including the production of replacement stacks needed over the 10 year system life. The carbon intensity of electricity generation from an SOFC was estimated to be 325–375 g/kWh, and is primarily determined by the operating efficiency as manufacturing only adds 10% to this. By displacing electricity generation in less efficient centralised power stations, operating an SOFC in UK homes would reclaim the energy and carbon from its manufacture in under 2 years; however, payback may not be possible if only high efficiency CCGT units are displaced. [Copyright &y& Elsevier]

Aquifer Thermal Energy Storage (ATES) is an underground thermal energy storage technology that provides large capacity (of order MW t h to 10s MW t h), low carbon heating and cooling to large buildings and building complexes, or district heating/cooling networks. The technology operates through seasonal capture, storage and re-use of thermal energy in shallow aquifers. ATES could make a significant contribution to decarbonising UK heating and cooling, but uptake is currently very low: eleven low temperature (LT-ATES) systems currently operating in the UK meet < 0.01% of the UK's heating and < 0.5% of cooling demand. The Wandsworth Riverside Quarter development in London is analysed as a successful UK case study. The UK has large potential for widespread deployment of LT-ATES, due to its seasonal climate and the wide availability of suitable aquifers co-located with urban centres of high heating and cooling demand. ATES could supply ca. 61% of UK heating demand, and ca. 79% of cooling demand with a 13%–41% reduction in carbon emissions for heating, and 70%–94% reduction for cooling, compared to equivalent ground- or air-sourced heat pump systems. However, problems with design and operation in some UK systems have caused sub-optimal performance. The UK can benefit from experience of both successful and unsuccessful deployments but these need to be more widely reported. Raising awareness, developing policies to encourage uptake, streamlining regulations and developing expertise are essential to unlock the potential of ATES technology in the UK, which requires engagement with policymakers, regulators, industry stakeholders and the general public. • Low UK uptake: 11 systems supply < 0.01% national heating and < 0.5% cooling demand. • Large growth potential to supply ca. 61% of UK heating and 79% of cooling demand. • Could reduce CO 2 emissions by 13%–41% for heating compared to rival technologies. • Potential for exceptional reductions of 70%–94% in CO 2 emissions for cooling. • Example of a successful UK installation demonstrates the technology is suitable. [ABSTRACT FROM AUTHOR]

International shipping faces strong challenges with new legally binding air quality regulations and a 50% decarbonisation target by 2050. Liquefied natural gas (LNG) is a widely used alternative to liquid fossil fuels, but methane emissions reduce its overall climate benefit. This study utilises new emissions measurements and supply-chain data to conduct a comprehensive environmental life cycle and cost assessment of LNG as a shipping fuel, compared to heavy fuel oil (HFO), marine diesel oil (MDO), methanol and prospective renewable fuels (hydrogen, ammonia, biogas and biomethanol). LNG gives improved air quality impacts, reduced fuel costs and moderate climate benefits compared to liquid fossil fuels, but with large variation across different LNG engine types. Methane slip from some engines is unacceptably high, whereas the best performing LNG engine offers up to 28% reduction in global warming potential when combined with the best-case LNG supply chain. Total methane emissions must be reduced to 0.8–1.6% to ensure climate benefit is realised across all timescales compared to current liquid fuels. However, it is no longer acceptable to merely match incumbent fuels; progress must be made towards decarbonisation targets. With methane emissions reduced to 0.5% of throughput, energy efficiency must increase 35% to meet a 50% decarbonisation target. • Environmental and cost assessment of LNG and other shipping fuels. • LNG improves air quality and cost but uncertain climate benefit over liquid fossil fuels. • Methane emissions must reduce to 0.8–1.6% to ensure a climate benefit over HFO. • If using LNG, ship efficiency must increase 35% to meet decarbonisation targets. [ABSTRACT FROM AUTHOR]

The recent effects of climate change and rising global warming levels have increased the need to transition towards clean energy. The use of multi-energy systems is one of the potential solutions to these issues, as validated in the literature. The production of hydrogen from cleaner sources has an integral role in decarbonizing the industrial, building, and transportation sectors. Hence, this study proposes novel multi-energy systems that can produce hydrogen from wind resources. The study is novel as it developed an innovative multi-energy system configuration and also considers hydrogen production as a means to utilize excess wind power production. The intermittency of wind resources has been a major drawback in using this renewable energy as the singular source for multi-generation systems. The multi-energy configuration developed and analyzed in this study proposed a solution for this by integrating a regenerative reheat biomass integrated power cycle as an auxiliary system for the multi-generation system (Wind-Bio-MGS). This system is modeled to produce electricity, heating, hot water, and hydrogen. The energy, exergy, and exergoeconomic approach is adopted in this study to evaluate the steady-state performance of the system, while the levelized cost of electricity (LCOE), levelized cost of heating (LCOh), and levelized cost of Hydrogen (LCOH) are also computed. A multi-objective optimization of the overall exergy efficiency and total product unit cost is presented. The parametric analysis of the energy systems is included to show the sensitivity of different parameters to changes and validate the robustness of the modeled system. The results show that the integration of hydrogen with wind-based multi-generation systems is a viable means of reducing carbon emissions and global warming. The overall energy and exergy efficiencies of the Wind-Bio-MGS system are 69.13% and 31.16%, respectively. The LCOE, LCOh, and LCOH for the system, respectively, are 0.02828 $ kWh−1, 0.004038 $ kWh−1, and 1.311 $ kg−1 s−1. [ABSTRACT FROM AUTHOR]

There is strong agreement across the energy modelling community that wind energy will be a key route to mitigating carbon emissions in the electricity sector. This paper presents a Geospatial Information System methodology for estimating spatially-resolved levelised cost of electricity for offshore wind, globally. The principal spatial characteristics of capital costs are transmission distance (i.e. the distance to grid connection) and water depth, because of the disparate costs of turbine foundation technologies. High resolution capacity factors are estimated from a bottom-up estimation of global wind speeds calculated from several decades of wind speed data. A technology-rich description of fixed and floating foundation types allows the levelised cost of electricity to be calculated for 1 × 1 km grid cells, relative to location-specific annual energy production, and accounting for exclusion areas, array losses and turbine availability. These data can be used to assess the economically viable offshore wind energy potential, globally and on a country basis, and can serve as inputs to energy systems models. • Global 1 × 1 km country-by-country cost estimation for offshore wind power. • A technology rich approach considering both fixed and floating structures. • Bottom-up estimation of levelized cost, including country-specific financing costs. • Results sensitive to annual energy production, capital cost and financing costs. • Offshore wind costs continue to decline since recent estimates. [ABSTRACT FROM AUTHOR]

Electric vehicles are now a major contributor to decarbonising the transport sector. Their rollout has accelerated rapidly since 2020, reaching a global fleet of 40 million in 2023. This presents both problems and opportunities for electricity systems, with charging increasing peak loads, but also providing a large new source of flexibility to help manage increased shares of wind and solar generation, shift peak demand and improve network management. While EV flexibility is widely discussed, there is uncertainty surrounding the magnitude to which EVs could help electricity systems, and a distinct lack of quantitative evidence around adoption, charging behaviour and technical capabilities for load shifting. This study employs the rapid evidence assessment method to synthesise recent information. We find that studies expect that EVs could provide 1–11 GW of flexible capacity per million vehicles (median: 3.7 GW), with the ability to shift demand by 1.5–5 h (median: 4 h) and a price elasticity of −0.77 to −0.10 (median: 0.15). Diurnal profiles of charging demand and availability for providing flexibility are aggregated across multiple studies. The results are relevant for energy modellers and show that the interaction between EVs and electricity systems can be generalised on a widely-applicable basis. • Quantitative evidence on flexibility to the electricity system from electric vehicles. • Rapid evidence assessment and data extraction methods. • Providing key reference data set for energy modellers. • Interactions of electric vehicles and electricity systems can be generalised. [ABSTRACT FROM AUTHOR]

The penetration of solar photovoltaic (PV) generation is increasing in many countries, with significant implications for the adequacy and operation of power systems. This work considers the Nord bidding zone within Italy, which hosts 7.7 GW of PV and almost no wind power. We simulate the implications of different PV penetration levels on the need for firm generation capacity and on ramping requirements over one to several hours. We compare ten years of synthetic hourly PV generation series derived from CM-SAF SARAH satellite data and observed load. The analysis also provides insights into the storage capacity required to smooth residual load over different time horizons. Results show that without storage (i) the penetration of PV in the region does not sensibly reduce the need for firm generation; (ii) the marginal contribution of PV to meet power demand decreases with its penetration; and (iii) high penetrations lead to larger and more frequent ramps, although extreme ramp rates do not last more than 1 h. The availability of storage significantly alters these results, but large storage capacities are required. Smoothing net load by a few hours requires 2–7 GWh of storage per GW of PV installed. [ABSTRACT FROM AUTHOR]

We present an power systems optimisation model for national-scale power supply capacity expansion considering endogenous technology cost reduction (ESO-XEL). The mixed-integer linear program minimises total system cost while complying with operational constraints, carbon emission targets, and ancillary service requirements. A data clustering technique and the relaxation of integer scheduling constraints is evaluated and applied to decrease the model solution time. Two cost learning curves for the different power technologies are derived: one assuming local learning effects, the other accounting for global knowledge spill-over. A piece-wise linear formulation allows the integration of the exponential learning curves into the ESO-XEL model. The model is applied to the UK power system in the time frame of 2015 to 2050. The consideration of cost learning effects moves optimal investment timings to earlier planning years and influences the competitiveness of technologies. In addition, the maximum capacity build rate parameter influences the share of power generation significantly; the possibility of rapid capacity build-up is more important for total system cost reduction by 2050 than accounting for technology cost reduction. [ABSTRACT FROM AUTHOR]

Decarbonising electricity systems is essential for mitigating climate change. Future systems will likely incorporate higher penetrations of intermittent renewable and inflexible nuclear power. This will significantly impact on system operations, particularly the requirements for flexibility in terms of reserves and the cost of such services. This paper estimates the interrelated changes in wholesale electricity and reserve prices using two novel methods. Firstly, it simulates the short run marginal cost of generation using a unit commitment model with post-processing to achieve realistic prices. It also introduces a new reserve price model, which mimics actual operation by first calculating the day ahead schedules and then letting deviations from schedule drive reserve prices. The UK is used as a case study to compare these models with traditional methods from the literature. The model gives good agreement with and historic prices in 2015. In a 2035 scenario, increased renewables penetration reduces mean electricity prices, and leads to price spikes due to expensive plants being brought online briefly to cope with net load variations. Contrary to views previously held in literature, a renewable intensive scenario does not lead to a higher reserve price than a fossil fuel intensive scenario. Demand response technology is shown to offer sizeable economic benefits when maintaining system balance. More broadly, this framework can be used to evaluate the economics of providing reserve services by aggregating decentralised energy resources such as heat pumps, micro-CHP and electric vehicles. [ABSTRACT FROM AUTHOR]

While the 2009 EU Renewables Directive allows countries to purchase some of their obligation from another member state, no country has yet done so, preferring to invest locally even where load factors are very low. If countries specialised in renewables most suited to their own endowments and expanded international trade, we estimate that system costs in 2030 could be reduced by 5%, or €15 billion a year, after allowing for the costs of extra transmission capacity, peaking generation and balancing operations needed to maintain electrical feasibility. Significant barriers must be overcome to unlock these savings. Countries that produce more renewable power should be compensated for the extra cost through tradable certificates, while those that buy from abroad will want to know that the power can be imported when needed. Financial Transmission Rights could offer companies investing abroad confidence that the power can be delivered to their consumers. They would hedge short-term fluctuations in prices and operate much more flexibly than the existing system of physical point-to-point rights on interconnectors. Using FTRs to generate revenue for transmission expansion could produce perverse incentives to under-invest and raise their prices, so revenues from FTRs should instead be offset against payments under the existing ENTSO-E compensation scheme for transit flows. FTRs could also facilitate cross-border participation in capacity markets, which are likely to be needed to reduce risks for the extra peaking plants required. [ABSTRACT FROM AUTHOR]

There is a need for efficient methods to simulate wind power output to assist the expected rapid uptake of new wind farms. Reanalysis products provide our best estimate for the previous state of the atmosphere and are popular due to their global coverage and convenience. However, these models are known to misestimate wind power output by up to ± 50% due to significant spatial biases. Previous work applied bias correction methods to improve power simulations. However, there has been no assessment of the spatial and temporal resolution that these bias correction factors should be derived at for the best accuracy. In this paper, we investigate the impact of the spatial and temporal resolution by grouping turbines into a varying number of clusters and varying the frequency at which correction factors are calculated across a year. The correction factors are used to simulate the power output of 4,834 turbines across Denmark resulting in monthly capacity factors. The best correction scenario decreased the error of simulated outputs by 43%. Increasing the spatial resolution of bias correction reduced the error by up to 11%. Correction factors with a bimonthly (every two months) frequency decreased the error by 3% from the time-independent correction factors. • Bias correction is typically applied to reanalysis datasets for wind power modelling. • Previous work employed very coarse spatio-temporal resolution when bias correcting. • We use high-resolution data from Denmark to bias correct at far higher resolution. • The resulting impact on wind power simulations is investigated. • The error in monthly simulated capacity factors is decreased by 43%. [ABSTRACT FROM AUTHOR]

[Display omitted] Understanding how to best integrate electric vehicles (EVs) into electricity systems is key to the success of both sectors. We pair national-scale EV charging data with high resolution electricity generation data for the UK to calculate the average and marginal emissions produced through charging EVs. Considering the average generation mix weighted by when charging occurs, a typical Battery EV (BEV) emitted 41 g CO 2 , 27 mg NO x and 0.7 mg PM 2.5 per kilometre in 2019. A static analysis using annual averages underestimates these values by 4 %. The 'marginal' emissions from BEV charging are 25 % higher than average emissions for CO 2 and NO x , and 50 % lower for PM 2.5. Smart charging was found to reduce average CO 2 emissions by 10 % when compared to the typically charged vehicle; however, smart charging strategies may increase marginal emissions. Future smart charging strategies should minimise marginal emissions and will require access to 24-hour opportunistic smart charging. [ABSTRACT FROM AUTHOR]

The global expansion of solar photovoltaics (PV) is central to the global energy transition. As governments aim to triple renewable energy capacity by 2030, solar PV is poised for rapid growth, particularly outside mid-latitude regions (China, Europe, US) where uptake has been highest. These new growth areas have diverse environmental conditions, where factors like higher temperatures and aerosol concentrations strongly impact solar power production. A comprehensive review of these effects therefore aids PV performance and siting optimization. This review examines six key influences: solar irradiance, ambient temperature, atmospheric conditions, terrain effects, extreme weather events, and long-term irradiance changes. First, solar irradiance has strong geographic and temporal variability, making it the most significant factor. Second, raising module temperature reduces efficiency by 0.4–0.5 % per degree Celsius, limiting productivity in hotter climates. Third, atmospheric conditions (clouds, aerosols, pollutants, and dust) can reduce electricity output by up to 60 %, especially in desert regions. Fourth, terrain factors like albedo and snow present mixed effects, with increased reflection boosting output but snow obstructing panels. Fifth, extreme weather like wildfires and hailstorms cause substantial damage, while solar eclipses lead to large but short-lived output losses. Finally, long-term changes in solar irradiance, driven by climate change and air pollutants, present future challenges for maintaining PV efficiency. Optimizing PV systems for diverse climates and mitigating environmental impacts on productivity is important to the continued success of solar photovoltaics. This review highlights the need for tailored strategies to maintain performance in varied and evolving environmental contexts. [Display omitted] • Environmental factors critically affect solar PV performance across diverse climates. • High temperatures reduce solar PV efficiency by 0.4–0.5 % per degree Celsius. • Dust can reduce PV output by up to 60 %, especially in desert regions. • Terrain factors like albedo and snow present mixed effects on PV energy generation. • Long-term climate change and extreme weather pose future challenges to PV systems. [ABSTRACT FROM AUTHOR]

Replacing fossil fuels with energy sources and carriers that are sustainable, environmentally benign, and affordable is amongst the most pressing challenges for future socio-economic development. To that goal, hydrogen is presumed to be the most promising energy carrier. Electrocatalytic water splitting, if driven by green electricity, would provide hydrogen with minimal CO2 footprint. The viability of water electrolysis still hinges on the availability of durable earth-abundant electrocatalyst materials and the overall process efficiency. This review spans from the fundamentals of electrocatalytically initiated water splitting to the very latest scientific findings from university and institutional research, also covering specifications and special features of the current industrial processes and those processes currently being tested in large-scale applications. Recently developed strategies are described for the optimisation and discovery of active and durable materials for electrodes that ever-increasingly harness first-principles calculations and machine learning. In addition, a technoeconomic analysis of water electrolysis is included that allows an assessment of the extent to which a large-scale implementation of water splitting can help to combat climate change. This review article is intended to cross-pollinate and strengthen efforts from fundamental understanding to technical implementation and to improve the 'junctions' between the field's physical chemists, materials scientists and engineers, as well as stimulate much-needed exchange among these groups on challenges encountered in the different domains. [ABSTRACT FROM AUTHOR]

The rapid uptake of renewable energy technologies in recent decades has increased the demand of energy researchers, policymakers and energy planners for reliable data on the spatial distribution of their costs and potentials. For onshore wind energy this has resulted in an active research field devoted to analysing these resources for regions, countries or globally. A particular thread of this research attempts to go beyond purely technical or spatial restrictions and determine the realistic, feasible or actual potential for wind energy. Motivated by these developments, this paper reviews methods and assumptions for analysing geographical, technical, economic and, finally, feasible onshore wind potentials. We address each of these potentials in turn, including aspects related to land eligibility criteria, energy meteorology, and technical developments of wind turbine characteristics such as power density, specific rotor power and spacing aspects. Economic aspects of potential assessments are central to future deployment and are discussed on a turbine and system level covering levelized costs depending on locations, and the system integration costs which are often overlooked in such analyses. Non-technical approaches include scenicness assessments of the landscape, constraints due to regulation or public opposition, expert and stakeholder workshops, willingness to pay/accept elicitations and socioeconomic cost-benefit studies. For each of these different potential estimations, the state of the art is critically discussed, with an attempt to derive best practice recommendations and highlight avenues for future research. • Review of over 300 studies on large-scale onshore wind potential assessments. • Analysis of geographic, technical, economic and 'feasible' potentials. • Identify weaknesses in methods and best practice examples. • Methods could improve transparency, validation, and sensitivities. • Further interdisciplinary research required on 'feasible' potentials. [ABSTRACT FROM AUTHOR]

A wind turbine's power curve relates its power production to the wind speed it experiences. The typical shape of a power curve is well known and has been studied extensively. However, power curves of individual turbine models can vary widely from one another. This is due to both the technical features of the turbine (power density, cut-in and cut-out speeds, limits on rotational speed and aerodynamic efficiency), and environmental factors (turbulence intensity, air density, wind shear and wind veer). Data on individual power curves are often proprietary and only available through commercial databases. We therefore develop an open-source model for pitch regulated horizontal axis wind turbine which can generate the power curve of any turbine, adapted to the specific conditions of any site. This can employ one of six parametric models advanced in the literature, and accounts for the eleven variables mentioned above. The model is described, the impact of each technical and environmental feature is examined, and it is then validated against the manufacturer power curves of 91 turbine models. Versions of the model are made available in MATLAB, R and Python code for the community. • A generic power curve model dependent on main turbine characteristics is proposed. • Main environmental parameters are considered. • A statistical analysis of the model inputs is proposed. • The modelled output is validated against numerous manufacturer power curves. • Versions of the model are made available in MATLAB, R and Python. [ABSTRACT FROM AUTHOR]

The energy–water–land nexus represents a critical leverage future policies must draw upon to reduce trade-offs between sustainable development objectives. Yet, existing long-term planning tools do not provide the scope or level of integration across the nexus to unravel important development constraints. Moreover, existing tools and data are not always made openly available or are implemented across disparate modeling platforms that can be difficult to link directly with modern scientific computing tools and databases. In this paper, we present the NExus Solutions Tool (NEST): a new open modeling platform that integrates multi-scale energy–water–land resource optimization with distributed hydrological modeling. The new approach provides insights into the vulnerability of water, energy and land resources to future socioeconomic and climatic change and how multi-sectoral policies, technological solutions and investments can improve the resilience and sustainability of transformation pathways while avoiding counterproductive interactions among sectors. NEST can be applied at different spatial and temporal resolutions, and is designed specifically to tap into the growing body of open-access geospatial data available through national inventories and the Earth system modeling community. A case study analysis of the Indus River basin in south Asia demonstrates the capability of the model to capture important interlinkages across system transformation pathways towards the United Nations' Sustainable Development Goals, including the intersections between local and regional transboundary policies and incremental investment costs from rapidly increasing regional consumption projected over the coming decades. [ABSTRACT FROM AUTHOR]

• Analyzing wind-hydrogen production synergy in multi-energy systems. • Modelling three renewable energy-based multi-energy systems' configurations. • Modelling multi-energy systems' production of electricity, cooling, hydrogen, and hot water. • Levelized cost of electricity as low as 0.03653 $/kWh for wind-hydrogen production. • Energy and exergy efficiency ranges from 55.26% and 78.73% and 27.05% to 58.51%. With rising temperatures, extreme weather events, and environmental challenges, there is a strong push towards decarbonization and an emphasis on renewable energy, with wind energy emerging as a key player. The concept of multi-energy systems offers an innovative approach to decarbonization, with the potential to produce hydrogen as one of the output streams, creating another avenue for clean energy production. Hydrogen has significant potential for decarbonizing multiple sectors across buildings, transport, and industries. This paper explores the integration of wind energy and hydrogen production, particularly in areas where clean energy solutions are crucial, such as impoverished villages in Africa. It models three systems: distinct configurations of micro-multi-energy systems that generate electricity, space cooling, hot water, and hydrogen using the thermodynamics and cost approach. System 1 combines a wind turbine, a hydrogen-producing electrolyzer, and a heat pump for cooling and hot water. System 2 integrates this with a biomass-fired reheat-regenerative power cycle to balance out the intermittency of wind power. System 3 incorporates hydrogen production, a solid oxide fuel cell for continuous electricity production, an absorption cooling system for refrigeration, and a heat exchanger for hot water production. These systems are modeled with Engineering Equation Solver, and analyzed based on energy and exergy efficiencies, and on economic metrics like levelized cost of electricity (LCOE), cooling (LCOC), refrigeration (LCOR), and hydrogen (LCOH) under steady-state conditions. A sensitivity analysis of various parameters is presented to assess the change in performance. Systems were optimized using a multi-objective method, with maximizing exergy efficiency and minimizing total product unit cost used as objective functions. The results show that System 1 achieves 79.78 % energy efficiency and 53.94 % exergy efficiency. System 2 achieves efficiencies of 55.26 % and 27.05 % respectively, while System 3 attains 78.73 % and 58.51 % respectively. The levelized costs for micro-multi-energy System 1 are LCOE = 0.04993 $/kWh, LCOC = 0.004722 $/kWh, and LCOH = 0.03328 $/kWh. For System 2, these values are 0.03653 $/kWh, 0.003743 $/kWh, and 0.03328 $/kWh. In the case of System 3, they are 0.03736 $/kWh, 0.004726 $/kWh, and 0.03335 $/kWh, and LCOR = 0.03309 $/kWh. The results show that the systems modeled here have competitive performance with existing multi-energy systems, powered by other renewables. Integrating these systems will further the sustainable and net zero energy system transition, especially in rural communities. [ABSTRACT FROM AUTHOR]

Climate change and geopolitical risks call for the rapid transformation of electricity systems worldwide, with Europe at the forefront. Wind and solar are the lowest cost, lowest risk, and cleanest energy sources, but their variability poses integration challenges. Combining both technologies and integrating regions with dissimilar generation patterns optimizes the trade-off between maximizing energy output and minimizing its variability, which respectively give the lowest levelized cost and lowest integration cost. We apply the Markowitz mean-variance framework to a rich multi-decade dataset of wind and solar productivity to quantify the potential benefits of spatially integration of renewables across European countries at hourly, daily and monthly timescales. We find that optimal cross-country coordination of wind and solar capacities across Europe's integrated electricity system increases capacity factor by 22% while reducing hourly variability by 26%. We show limited benefits to solar integration due to consistent output profiles across Europe. Greater wind integration yields larger benefits due to the diversity of regional weather patterns. This framework shows the importance of considering renewable projects not in isolation, but as interconnected parts of a pan-continental system. Our results can guide policymakers towards strategic energy plans that reduce system-wide costs of renewable electricity, accelerating the clean energy transition. • Optimizing wind-solar installed capacities increases mean capacity factor and reduces its variability. • Combining wind and solar improves the output-variability tradeoff at all timescales. • The EU reference scenarios appear to overlook these substantial benefits. • Optimizing Europe's renewables increases output by 22% with 26% lower variability. [ABSTRACT FROM AUTHOR]

The decarbonisation of industry, heating and transportation is a major challenge for many countries' energy transition. Hydrogen is a direct low-carbon fuel alternative to natural gas offering a higher flexibility in the range of possible applications, yet currently most hydrogen is produced using carbon-intensive steam methane reforming due to cost considerations. Therefore, this study explores the economics of a prominent low-carbon method of hydrogen production, comparing the cost of hydrogen generation from offshore wind farms with and without grid electricity imports to conventional hydrogen production methods. A novel techno-economic model for offshore electrolysis production costs is presented, which makes hydrogen production fully dispatchable, leveraging geological salt-cavern storage. This model determines the lifetime costs aportioned across the system components, as well as the Levelised Cost of Hydrogen (LCOH). Using the United Kingdom as a case study, LCOH from offshore wind power is calculated to be €8.68/kg H2 using alkaline electrolysis (AEL), €10.49/kg H2 using proton exchange membrane electrolysis (PEMEL), and €10.88/kg H2 with grid electricity to backup the offshore wind power. A stochastic Monte-Carlo model is used to asses the uncertainty on costs and identify the cost of capital, electrolyser and wind farm capital costs, and cost of electricity as the most important drivers of LCOH across the different scenarios. Reducing the capital cost to comparative levels observed on today's wind farms alone, could see AEL LCOH fall to €5.32/kg H2 , near competitive with conventional generation methods. • Development of a techno-economic model for offshore electrolysis production cost. • Lifetime hydrogen production and Levelized cost of gas (LCOH) are determined. • LCOH is calculated using deterministic and stochastic Monte-Carlo models. • Alkaline electrolysis with offshore wind power cost is the UK's lowest cost option. [ABSTRACT FROM AUTHOR]

The energy-water-land nexus represents a critical leverage future policies must draw upon to reduce trade-offs between sustainable development objectives. Yet, existing long-term planning tools do not provide the scope or level of integration across the nexus to unravel important development constraints. Moreover, existing tools and data are not always made openly available or are implemented across disparate modeling platforms that can be difficult to link directly with modern scientific computing tools and databases. In this paper, we present the Nexus Solutions Tool (NEST): a new open modeling platform that integrates multi-scale energy-water-land resource optimization with distributed hydrological modeling. The new approach provides insights into the vulnerability of water, energy and land resources to future socioeconomic and climatic change and how multi-sectoral policies, technological solutions and investments can improve the resilience and sustainability of transformation pathways while avoiding counterproductive interactions among sectors. NEST can be applied at different spatial and temporal resolutions, and is designed specifically to tap into the growing body of open access geospatial data available through national inventories and the earth system modeling community. A case study analysis of the Indus River Basin in South Asia demonstrates the capability of the model to capture important interlinkages across system transformation pathways towards the United Nations' Sustainable Development Goals, including the intersections between local and regional transboundary policies and incremental investment costs from rapidly increasing regional consumption projected over the coming decades. [ABSTRACT FROM AUTHOR]

Highlights • Assessment of fuels, efficiency measures and policies to decarbonise shipping. • LNG must be combined with various efficiency measures to meet 50% climate target. • Slow steaming and wind assistance are key efficiency measures to reduce fuel. • Hydrogen and biofuels are lower carbon, but highly variable supply chain emissions. • Longer term deep decarbonisation will require strong economic incentives. Abstract International shipping provides 80–90% of global trade, but strict environmental regulations around NO X , SO X and greenhouse gas (GHG) emissions are set to cause major technological shifts. The pathway to achieving the international target of 50% GHG reduction by 2050 is unclear, but numerous promising options exist. This study provides a holistic assessment of these options and their combined potential to decarbonise international shipping, from a technology, environmental and policy perspective. Liquefied natural gas (LNG) is reaching mainstream and provides 20–30% CO 2 reductions whilst minimising SO X and other emissions. Costs are favourable, but GHG benefits are reduced by methane slip, which varies across engine types. Biofuels, hydrogen, nuclear and carbon capture and storage (CCS) could all decarbonise much further, but each faces significant barriers around their economics, resource potentials and public acceptability. Regarding efficiency measures, considerable fuel and GHG savings could be attained by slow-steaming, ship design changes and utilising renewable resources. There is clearly no single route and a multifaceted response is required for deep decarbonisation. The scale of this challenge is explored by estimating the combined decarbonisation potential of multiple options. Achieving 50% decarbonisation with LNG or electric propulsion would likely require 4 or more complementary efficiency measures to be applied simultaneously. Broadly, larger GHG reductions require stronger policy and may differentiate between short- and long-term approaches. With LNG being economically feasible and offering moderate environmental benefits, this may have short-term promise with minor policy intervention. Longer term, deeper decarbonisation will require strong financial incentives. Lowest-cost policy options should be fuel- or technology-agnostic, internationally applied and will require action now to ensure targets are met by 2050. [ABSTRACT FROM AUTHOR]