180 results found
Giarola S, Mittal S, Vielle M, et al., 2021, Challenges in the harmonisation of global integrated assessment models: a comprehensive methodology to reduce model response heterogeneity, Science of the Total Environment, Vol: 783, ISSN: 0048-9697
Harmonisation sets the ground to a solid inter-comparison of integrated assessment models. A clear and transparent harmonisation process promotes a consistent interpretation of the modelling outcomes divergences and, reducing the model variance, is instrumental to the use of integrated assessment models to support policy decision-making. Despite its crucial role for climate economic policies, the definition of a comprehensive harmonisation methodology for integrated assessment modelling remains an open challenge for the scientific community.This paper proposes a framework for a harmonisation methodology with the definition of indispensable steps and recommendations to overcome stumbling blocks in order to reduce the variance of the outcomes which depends on controllable modelling assumptions. The harmonisation approach of the PARIS REINFORCE project is presented here to layout such a framework. A decomposition analysis of the harmonisation process is shown through 6 integrated assessment models (GCAM, ICES-XPS, MUSE, E3ME, GEMINI-E3, and TIAM). Results prove the potentials of the proposed framework to reduce the model variance and present a powerful diagnostic tool to feedback on the quality of the harmonisation itself.
Balcombe P, Staffell I, Kerdan IG, et al., 2021, How can LNG-fuelled ships meet decarbonisation targets? An environmental and economic analysis, Energy, Vol: 227, Pages: 1-12, ISSN: 0360-5442
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.
Grant N, Hawkes A, Mittal S, et al., 2021, Confronting mitigation deterrence in low-carbon scenarios, Environmental Research Letters
Giarola S, Molar-Cruz A, Vaillancourt K, et al., 2021, The role of energy storage in the uptake of renewable energy: a model comparison approach, Energy Policy, Vol: 151, ISSN: 0301-4215
The power sector needs to ensure a rapid transition towards a low-carbon energy system to avoid the dangerous consequences of greenhouse gas emissions. Storage technologies are a promising option to provide the power system with the flexibility required when intermittent renewables are present in the electricity generation mix. This paper focuses on the role of electricity storage in energy systems with high shares of renewable sources. The study encompasses a model comparison approach where four models (GENeSY S-MOD, MUSE, NAT EM, and urbs−MX) are used to analyse the storage uptake in North America. The analysis addresses the conditions affecting storage uptake in each country and its dependence on resource availability, technology costs, and public policies. Results show that storage may promote emissions reduction at lower costs when renewable mandates are in place whereas in presence of carbon taxes, renewables may compete with other low-carbon options. The study also highlights the main modelling approach shortcomings in the modelling of electricity storage in integrated assessment models.
Sechi S, Giarola S, Lanzini A, et al., 2021, A bottom-up appraisal of the technically installable capacity ofbiogas-based solid oxide fuel cells for self power generation in wastewatertreatment plants, Journal of Environmental Management, Vol: 279, Pages: 1-15, ISSN: 0301-4797
This paper proposes a bottom-up method to estimate the technical capacity of solid oxide fuel cells to be installed in wastewater treatment plants and valorise the biogas obtained from the sludge through an efficient conversion into electricity and heat. The methodology uses stochastic optimisation on 200 biogas profile scenarios generated from industrial data and envisages a Pareto approach for an a posteriori assessment of the optimal number of generation unit for the most representative plant configuration sizes. The method ensures that the dominant role of biogas fluctuation is included in the market potential and guarantees that the utilization factor of the modules remains higher than 70% to justify the investment costs. Results show that the market potential for solid oxide fuel cells across Europe would lead up to 1,300 MW of installed electric capacity in the niche market of wastewater treatment and could initiate a capital and fixed costs reduction which could make the technology comparable with alternative combined heat and power solutions.
Nikas A, Gambhir A, Trutnevyte E, et al., 2021, Perspective of comprehensive and comprehensible multi-model energy and climate science in Europe, Energy, Vol: 215, Pages: 1-8, ISSN: 0360-5442
Europe’s capacity to explore the envisaged pathways that achieve its near- and long-term energy and climate objectives needs to be significantly enhanced. In this perspective, we discuss how this capacity is supported by energy and climate-economy models, and how international modelling teams are organised within structured communication channels and consortia as well as coordinate multi-model analyses to provide robust scientific evidence. Noting the lack of such a dedicated channel for the highly active yet currently fragmented European modelling landscape, we highlight the importance of transparency of modelling capabilities and processes, harmonisation of modelling parameters, disclosure of input and output datasets, interlinkages among models of different geographic granularity, and employment of models that transcend the highly harmonised core of tools used in model inter-comparisons. Finally, drawing from the COVID-19 pandemic, we discuss the need to expand the modelling comfort zone, by exploring extreme scenarios, disruptive innovations, and questions that transcend the energy and climate goals across the sustainability spectrum. A comprehensive and comprehensible multi-model framework offers a real example of “collective” science diplomacy, as an instrument to further support the ambitious goals of the EU Green Deal, in compliance with the EU claim to responsible research.
Oluleye G, Gandiglio M, Santarelli M, et al., 2021, Pathways to commercialisation of biogas fuelled solid oxide fuel cells in European wastewater treatment plants, Applied Energy, Vol: 282, ISSN: 0306-2619
Fuel cell developments are driven by the need for more efficient and cleaner energy provision; however, current costs make it uneconomic in wastewater treatment plants. Interventions via policy instruments and business models may be required for cost reduction until the fuel cell is driven purely by market forces. In this work a novel market potential assessment methodology is developed and applied to quantify the impact of various interventions on biogas fuelled solid oxide fuel cell cost reduction and synthesize pathways to its commercialisation. The method is applied to 6181 plants in 27 European countries. Results show that 71% cost reduction is required for a medium sized fuel cell to be market driven. Existing incentives can trigger cost reduction by 13–38% but are not able to sustain it until the fuel cell is market driven. Innovations in business models, and incentivising business models instead of technologies can trigger and sustain cost reduction. Results also show that under today’s high capital cost, the number of economically attractive plants required to install fuel cells are lowest when business models are incentivised compared to other interventions. Incentivising new business models to encourage innovation in the sector has more impact that incentivising technologies. The framework is also relevant for creating narratives around the commercialisation of new technologies.
García Kerdan I, Giarola S, Skinner E, et al., 2020, Modelling future agricultural mechanisation of major crops in China: an assessment of energy demand, land use and emissions, Energies, Vol: 13, Pages: 6636-6636, ISSN: 1996-1073
Agricultural direct energy use is responsible for about 1–2% of global emissions and is the major emitting sector for methane (2.9 GtCO2eq y−1) and nitrous oxide (2.3 GtCO2eq y−1). In the last century, farm mechanisation has brought higher productivity levels and lower land demands at the expense of an increase in fossil energy and agrochemicals use. The expected increase in certain food and bioenergy crops and the uncertain mitigation options available for non-CO2 emissions make of vital importance the assessment of the use of energy and the related emissions attributable to this sector. The aim of this paper is to present a simulation framework able to forecast energy demand, technological diffusion, required investment and land use change of specific agricultural crops. MUSE-Ag & LU, a novel energy systems-oriented agricultural and land use model, has been used for this purpose. As case study, four main crops (maize, soybean, wheat and rice) have been modelled in mainland China. Besides conventional direct energy use, the model considers inputs such as fertiliser and labour demand. Outputs suggest that the modernisation of agricultural processes in China could have the capacity to reduce by 2050 on-farm emissions intensity from 0.024 to 0.016 GtCO2eq PJcrop−1 (−35.6%), requiring a necessary total investment of approximately 319.4 billion 2017$US.
Chu C-T, Hawkes AD, 2020, Optimal mix of climate-related energy in global electricity systems, Renewable Energy, Vol: 160, Pages: 955-963, ISSN: 0960-1481
Existing studies on high renewable share electricity systems are usually based on least cost optimization. Running the related models can be time-consuming when space-time resolution is high. This study investigates the optimal mix of climate-related energies for most countries in the world with optimization models based on three criteria: cost, residual load variability, and portfolio output variability. The objectives of minimizing residual load variability and portfolio output variability are to ensure the overall complementarity of the generation portfolio, which may result in less conventional dispatchable units needed in a system. Compromise solutions based on the three objectives are proposed as the optimal mix. This method can produce solutions in acceptable modelling time, and considers the portfolio output characteristics which can make higher climate-related energy penetration more practical. The results show that the compromise solutions can effectively minimize the three objective values in most countries. The results also suggest that wind power is crucial in higher renewable share systems while solar power does not reach over 50% capacity share.
Gerber Machado P, Rodrigues Teixeira AC, Mendes de Almeida Collaço F, et al., 2020, Assessment of greenhouse gases and pollutant emissions in the road freight transport sector: a case study for São Paulo state, Brazil, Energies, Vol: 13, Pages: 5433-5433, ISSN: 1996-1073
This study analyzes the road freight sector of São Paulo state to identify the best options to reduce greenhouse gases emissions and local pollutants, such as particulate matter, nitrogen oxides, carbon monoxide, and hydrocarbons. Additionally, the investment cost of each vehicle is also analyzed. Results show that electric options, including hybrid, battery, and hydrogen fuel-cell electric vehicles represent the best options to reduce pollutants and greenhouse gases emissions concomitantly, but considerable barriers for their deployment are still in place. With little long-term planning on the state level, electrification of the transport system, in combination with increased renewable electricity generation, would require considerable financial support to achieve the desired emissions reductions without increasing energy insecurity.
Sesini M, Giarola S, Hawkes AD, 2020, The impact of liquefied natural gas and storage on the EU natural gas infrastructure resilience, Energy, Vol: 209, Pages: 1-13, ISSN: 0360-5442
As the energy system progresses towards full decarbonization, natural gas could play an important role in it with its relatively low carbon characteristics and its abundant supply. At the core of the paper is a modelling analysis of the European Union (EU) natural gas network resilience in case of short-term supply disruption or unexpected increase in demand. The adopted linear programming model solves for the most cost effective transmission of gas flows, capacity and storage utilization in an interconnected EU gas system. Results presented in the paper show a significant increase in liquefied natural gas (LNG) costs (+40%) when commodity price increases (+40%) and LNG prices decreases (−20%), and an equally significant decline in transport and LNG costs (−30%,-50%) when storage volumes varies (−35%,+35%).The analysis highlights a complementary role between LNG and storage in ensuring a cost-effective response to a natural gas supply shock. It also indicates that LNG alone is inadequate in providing system resilience in case of an emergency in supply, stressing the importance of storage in the gas market and its intrinsic value in the system. The study emphasizes the need to further investigate the reliability and value of gas storage to reinforce energy security in Europe.
Budinis S, Sachs J, Giarola S, et al., 2020, An agent-based modelling approach to simulate the investment decision of industrial enterprises, Journal of Cleaner Production, Vol: 267, ISSN: 0959-6526
China is the leading ammonia producer and relies on a coal-based technology which makes the already energy intensive Haber-Bosch process, one of the most emission intensive in the world. This work is the first to propose an agent-based modelling framework to model the Chinese ammonia industry as it characterises the specific goals and barriers towards fuel switching and carbon capture and storage adoption for small, medium, and large enterprises either private or state-owned. The results show that facilitated access to capital makes investments in sustainable technologies more attractive for all firms, especially for small and medium enterprises. Without policy instruments such as carbon price, the decrease in emissions in the long-term is due to investments in natural gas-based technologies, as they typically have lower capital and operating costs, and also lower electricity consumption than coal-based production. Conversely, with policy instruments in place, a strong decrease in emissions occurs between 2060 and 2080 due to investors choosing natural gas and biomethane-based technologies, with carbon capture and storage. In the long term, natural gas and biomethane could compete, with the outcome depending on infrastructure, supply chain availability and land use constraints.
Moya D, Budinis S, Giarola S, et al., 2020, Agent-based scenarios comparison for assessing fuel-switching investment in long-term energy transitions of the India’s industry sector, Applied Energy, Vol: 274, Pages: 1-26, ISSN: 0306-2619
This paper presents the formulation and application of a novel agent-based integrated assessment approach to model the attributes, objectives and decision-making process of investors in a long-term energy transition in India’s iron and steel sector. It takes empirical data from an on-site survey of 108 operating plants in Maharashtra to formulate objectives and decision-making metrics for the agent-based model and simulates possible future portfolio mixes. The studied decision drivers were capital costs, operating costs (including fuel consumption), a combination of capital and operating costs, and net present value. Where investors used a weighted combination of capital cost and operating costs, a natural gas uptake of ~12PJ was obtained and the highest cumulative emissions reduction was obtained, 2 Mt CO2 in the period from 2020 to 2050. Conversely if net present value alone is used, cumulative emissions reduction in the same period was lower, 1.6 Mt CO2, and the cumulative uptake of natural gas was equal to 15PJ. Results show how the differing upfront investment cost of the technology options could cause prevalence of high-carbon fuels, particularly heavy fuel oil, in the final mix. Results also represent the unique heterogeneity of fuel-switching industrial investors with distinct investment goals and limited foresight on costs. The perception of high capital expenditures for decarbonisation represents a significant barrier to the energy transition in industry and should be addressed via effective policy making (e.g. carbon policy/price).
Huntington HG, Bhargava A, Daniels D, et al., 2020, Key findings from the core North American scenarios in the EMF34 intermodel comparison, Energy Policy, Vol: 144, Pages: 1-23, ISSN: 0301-4215
Within Canada, Mexico or the United States, policy-making organizations are evaluating energy markets and energy trade within their own borders often by ignoring how these countries’ energy systems are integrated with each other. These analytical gaps provided the main motivation for the Energy Modeling Forum (EMF) 34 study on North American energy integration and trade. This paper compares North American results from 17 models and discusses their policy motivation. Oil and natural gas production in the three major countries are modestly sensitive to crude oil and natural gas price changes, although these elasticities are below unity. Carbon taxes displace coal and some natural gas with renewables within all three power markets. Lower natural gas prices replace coal and some renewables with natural gas within electric generation. Higher intermittent renewable penetration in the power sector displaces coal and some natural gas. A key conclusion is that much remains to be done in integrating future analyses and in sharing and improving the quality and consistency of the underlying data.
Gerber Machado P, Tomei J, Hawkes A, et al., 2020, A simulator to determine the evolution of disparities in food consumption between socio-economic groups: A Brazilian case study, Sustainability, Vol: 12, Pages: 6132-6132, ISSN: 2071-1050
Food is a fundamental right that deserves attention but is usually dealt with from the supply side in aggregated models that use macroeconomic variables to forecast the demand and the required supply. This study challenges this paradigm by developing a simulator to analyze food consumption from the demand side and estimate the evolution of disparity in food consumption over time with respect to region, sex, ethnicity, education, and income. This novel approach was applied to Brazil using household expenditure surveys to feed serial neural networks. Results show that the ‘poorer’ north and northeast of Brazil encounter the lowest consumption of food and are therefore the most food vulnerable regions. This trend continues to 2040. The ‘richer’ south and southeast regions have higher food consumption, which varies according to sex, ethnicity, education, and income. Brazil has contrasting issues with some groups having considerably higher food consumption, while other groups still have less than the threshold for healthy consumption. Now, the country not only has to deal with the food access by the most vulnerable due to the latest economic declines but also to deal with excess consumption, the so-called “double burden of malnutrition”.
Speirs J, Jalil-Vega F, Cooper J, et al., 2020, The flexibility of gas - what is it worth?, White Paper 5: The Flexibility of gas – what is it worth?, London, UK, Publisher: Sustainable Gas Institute, Imperial College London, 5
What is the evidence on the flexibility value that gas vectors and gas networks can provide to support the future energy system?There is an increasing debate regarding the use of gas networks in providing support for the decarbonisation of energy systems.The perceived value of gas “vectors” – encompassing natural gas, hydrogen and biomethane – is that they may provide flexibility, helping to support daily and seasonal variation in energy demand, and increasingly intermittent electricity supply as renewable electricity generation increases as a proportion of the electricity mix.Arguments in support of gas suggest that electricity systems will find it difficult to maintain flexibility on their own, whilst also reducing greenhouse gas emissions and increasing production to meet new demand for heating and transport. Gas, on the other hand, is expected to provide flexibility at relatively low cost, and may be produced and used with relatively low greenhouse gas emissions.White Paper 5 investigates the evidence surrounding the flexibility provided by gas and gas networks and the cost of, and value provided by gas to the future energy system.
Realmonte G, Drouet L, Gambhir A, et al., 2020, Reply to "High energy and materials requirement for direct air capture calls for further analysis and R&D", NATURE COMMUNICATIONS, Vol: 11, ISSN: 2041-1723
Miu LM, Hawkes A, 2020, Private landlords and energy efficiency: Evidence for policymakers from a large-scale study in the United Kingdom, Energy Policy, Vol: 142, ISSN: 0301-4215
Energy use in British homes is a significant contributor to national greenhouse gas emissions, and the improvement of energy efficiency in residential buildings has long been an important topic in policy discussions. The lack of investment in energy-saving measures is particularly challenging in the private rented sector, and there are significant research and data gaps in understanding the retrofit behaviour of private landlords. In this study, we present the results of a detailed survey on retrofit behaviour of 1069 British private landlords. The survey assesses the engagement of landlords with 18 different energy efficiency measures, as well as their attitudes, perceptions, norms and a number of other characteristics. We use the data collected in the survey to produce 7 behavioural “typologies” of landlord retrofitters, by clustering respondents based on their socio-demographic and business characteristics. In addition to providing descriptive evidence of landlords' retrofit behaviour, our results reveal a number of opportunities for segmenting the landlord population into target groups for future policy interventions. By tailoring retrofit incentives to the needs and motivations of these groups, policy-makers can effectively engage landlords with specific energy-saving technologies, increasing the likelihood of retrofit uptake and accelerating the transition to an energy-efficient private rented sector.
Grant N, Hawkes A, Napp T, et al., 2020, The appropriate use of reference scenarios in mitigation analysis, Nature Climate Change, Vol: 10, Pages: 605-610, ISSN: 1758-678X
Comparing emissions scenarios is an essential part of mitigation analysis, as climate targets can be met in various ways with different economic, energy system and co-benefit implications. Typically, a central ‘reference scenario’ acts as a point of comparison, and often this has been a no policy baseline with no explicit mitigative action taken. The use of such baselines is under increasing scrutiny, raising a wider question around the appropriate use of reference scenarios in mitigation analysis. In this Perspective, we assess three critical issues relevant to the use of reference scenarios, demonstrating how different policy contexts merit the use of different scenarios. We provide recommendations to the modelling community on best practice in the creation, use and communication of reference scenarios.
Garcia Kerdan I, Giarola S, Hawkes A, 2020, Implications of future natural gas demand on sugarcane production, land use Change and related emissions in Brazil, Journal of Sustainable Development of Energy, Water and Environment Systems, Vol: 8, Pages: 304-327, ISSN: 1848-9257
Due to its low share of energy-related emissions, energy systems models have overlooked the implications of technological transition in the agricultural sector and its interaction in the wider energy system. This paper explores the role of agriculture intensification by using a novel agricultural-based energy systems model. The aim is to explore the future role of Brazil’s agriculture and its dynamics with other energy sectors under two carbon constraint scenarios. The main focus has been to study resource competition between sugarcane and natural gas at a country level. Results show that in order to meet the future food and bioenergy demand, the agricultural sector would start intensifying by 2030, improving productivity at the expense of higher energy demand, however, land-related emissions would be minimised due to freed-up pasture land and reduction in deforestation rates. Additionally, the development of balanced bioenergy and natural gas markets may help limit the sugarcane expansion rates, preserving up to 12.6 million hectares of forest land, with significant emissions benefits.
Lyrio de Oliveira L, García Kerdan I, de Oliveira Ribeiro C, et al., 2020, Modelling the technical potential of bioelectricity production under land use constraints: A multi-region Brazil case study, Renewable and Sustainable Energy Reviews, Vol: 123, Pages: 1-15, ISSN: 1364-0321
In Brazil, bioelectricity generation from sugarcane bagasse and black liquor is regarded as a sustainable electricity supply option. However, questions regarding land use, investment decisions, and demand for paper, ethanol and sugar make its future role uncertain. The aim of this paper is to present a novel modelling framework based on a soft-link between a multi-sectoral Brazilian integrated assessment model (MUSE-Brazil) and an electricity portfolio optimisation model (EPOM). The proposed framework is capable of dynamically simulating sectoral electricity demand, regional bioenergy production under land use constraints and optimal power sector technological shares in each of the electricity subsystems. Considering Brazil under a 2 °C carbon budget, two scenarios based on economic attractiveness of producing second-generation ethanol have been investigated. Under the scenario where second-generation ethanol is not produced, outputs indicate that by 2050, Brazil would increase sugarcane and wood production by 68% and 49% respectively without causing direct or indirect deforestation. Agriculture intensification is evidenced as an alternative for reducing land use disruptions. Bioelectricity share is projected to remain around 9–10%. However, if second generation ethanol becomes cost-effective, thus limiting bagasse availability, the share of bioelectricity production would decrease to approximately 7.7%, with natural gas-fired plants playing a stronger role in the future power system expansion, causing an increase on electricity sector emissions.
Jalil Vega F, Garcia Kerdan I, Hawkes A, 2020, Spatially-resolved urban energy systems model to study decarbonisation pathways for energy services in cities, Applied Energy, Vol: 262, ISSN: 0306-2619
This work presents the COMET (Cities Optimisation Model for Energy Technologies) model, a spatially-resolved urban energy systems model that takes into account energy service demands for heating, cooling, electricity, and transport, and finds cost-effective pathways for supplying these demands under carbon constraints, trading-off energy supply, network infrastructure, and end-use technologies. Spatially-resolved energy service demands were obtained for the city of Sao Paulo, and six scenarios were modelled. Results show that district cooling is cost-effective in the highest linear cooling density zones, with full penetration in zones with over 1100 kWh/m by 2050. This threshold diminishes with tighter carbon constraints. Heating is electrified in all scenarios, with electric boilers and air-source heat pumps being the main supply technologies for the domestic and commercial sectors respectively by 2050. In the most carbon constrained scenario with a medium decarbonised electricity grid, ground source heat pumps and hydrogen boilers appear as transition technologies between 2030 and 2045 for the commercial and domestic sectors respectively, reaching 95% and 40% of each sector’s heat installed capacity in 2030. In the transport sector, ethanol cars replace gasoline, diesel, and compressed natural gas cars; compressed natural gas buses replace diesel and electric buses; and lorries continue using diesel. In carbon constrained scenarios, higher penetrations of electric cars and buses are obtained, while no change is observed for lorries. Finally, the most expensive scenario was only 6% more expensive than the reference scenario, meaning that achieving decarbonisation targets is not much costlier when comparing scenarios from a system-wide perspective.
Chu C-T, Hawkes AD, 2020, A geographic information system-based global variable renewable potential assessment using spatially resolved simulation, Energy, Vol: 193, Pages: 1-11, ISSN: 0360-5442
Variable renewable energy is set to become a key energy source worldwide, but there is concern regarding the impact of the intermittency of its output when penetration is high. Energy system models need to tackle this issue by improving modelling resolution and scope. To allow for such modelling, more and better input datasets are needed on variable renewable energy potentials and yields. These need to be of global scope, of sufficient spatial and temporal resolution, and generated with transparent, consistent methods. This study develops the methods and applies it to generate these datasets at subnational and hourly resolution. The assessment is carried out for wind and solar technologies with consistent constraints including geographical, social and economic aspects. Features from the OpenStreetMap are converted into land cover and land use datasets and applied. Hourly energy output is simulated using NASA MERRA-2 meteorological datasets, reconciled with resource maps from the Global Wind Atlas and Global Solar Atlas platforms. Capacity supply curves are provided for 731 terrestrial zones and 339 offshore zones worldwide, along with corresponding hourly output profiles over a 10-year simulation period. The proposed energy potentials are relative conservative compared with other studies. The datasets can serve as input for regional or global energy system models when analyzing high variable renewable energy shares.
Luh S, Budinis S, Giarola S, et al., 2020, Long-term development of the industrial sector – case study about electrification, fuel switching, and CCS in the USA, Computers & Chemical Engineering, Vol: 133, Pages: 1-14, ISSN: 0098-1354
In the urgent quest for solutions to mitigate climate change, the industry is one of the most challenging sectors to decarbonize. In this work, a novel simulation framework is presented to model the investment decisions in industry, the Industrial Sector Module (ISM) of the ModUlar energy system Simulation Environment (MUSE). This work uses the ISM to quantify effects of three combined measures for CO2 emission reduction in industry, i.e. fuel switching, electrification, and adoption of Carbon Capture and Storage (CCS) and to simulate plausible scenarios (base scenario and climate ambitious scenario) for curbing emissions in the iron and steel sector in the USA between 2010 and 2050. Results show that when the climate ambitious scenario is applied, the cumulative emissions into the atmosphere (2,158 Mt CO2) are reduced by 40% in comparison to the base scenario (3,608 Mt CO2). This decarbonization gap between both scenarios intensifies over time; in the year 2050, the CO2 intensity in the climate ambitious scenario is 81% lower in comparison to the base scenario. The study shows that major contributions to industry decarbonization can come from the further uptake of secondary steel production. Results show also that a carbon tax drives the decarbonization process but is not sufficient on its own. In addition, the uptake of innovative low-carbon breakthrough technologies is necessary. It is concluded that industrial electrification is counterproductive for climate change mitigation, if electricity is not provided by low-carbon sources. Overall, fuel switching, industrial electrification, and CCS adoption as single measures have a limited decarbonization impact, compared to an integrated approach that implements all the measures together providing a much more attractive solution for CO2 mitigation.
Bosch J, Staffell I, Hawkes AD, 2019, Global levelised cost of electricity from offshore wind, Energy, Vol: 189, Pages: 116357-116357, ISSN: 0360-5442
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.
García Kerdan I, Jalil-Vega F, Toole J, et al., 2019, Modelling cost-effective pathways for natural gas infrastructure: A southern Brazil case study, Applied Energy, Vol: 255, ISSN: 0306-2619
Currently, natural gas in Brazil represents around 12.9% of the primary energy supply, with consistent annual growth during the last decade. However, Brazil is entering a time of uncertainty regarding future gas supply, mainly as import from Bolivia is being renegotiated. As such, diversification of gas supply sources and routes need to be considered. Energy systems and infrastructure models are essential tools in assisting energy planning decisions and policy programmes at regional and international levels. In this study, a novel combination of a simulation-based integrated assessment model (MUSE-South_Brazil) and the recently-developed Gas INfrastructure Optimisation model (GINO) is presented. The Brazilian region represented by the five southern states served by the Bolivian gas pipeline (GASBOL) has been investigated. Modelled projections suggest that regional gas demand would increase from 38.8 mcm/day in 2015 to 104.3 mcm/day by 2050, mainly driven by the increasing demand in the industry and power sectors. Therefore existing regional gas infrastructure would be insufficient to cover future demands. Three different renegotiation scenarios between Brazil and Bolivia were modelled, obtaining distinct cost-optimal infrastructure expansion pathways. Depending on the scenario, the model expects gas demand to be covered by other supply options, such as an increase in pre-salt production, LNG imports and imports from a new Argentinian pipeline.
Trutnevyte E, Hirt LF, Bauer N, et al., 2019, Societal transformations in models for energy and climate policy: The ambitious next step, One Earth, Vol: 1, Pages: 423-433, ISSN: 2590-3322
Whether and how long-term energy and climate targets can be reached depend on a range of interlinked factors: technology, economy, environment, policy, and society at large. Integrated assessment models of climate change or energy-system models have limited representations of societal transformations, such as behavior of various actors, transformation dynamics in time, and heterogeneity across and within societies. After reviewing the state of the art, we propose a research agenda to guide experiments to integrate more insights from social sciences into models: (1) map and assess societal assumptions in existing models, (2) conduct empirical research on generalizable and quantifiable patterns to be integrated into models, and (3) build and extensively validate modified or new models. Our proposed agenda offers three benefits: interdisciplinary learning between modelers and social scientists, improved models with a more complete representation of multifaceted reality, and identification of new and more effective solutions to energy and climate challenges.
da Hora MABP, Asrilhant B, Accioly RMS, et al., 2019, Decision making to book oil reserves for different Brazilian fiscal agreements using dependence structure, ENERGY STRATEGY REVIEWS, Vol: 26, ISSN: 2211-467X
Miu LM, Mazur CM, Van Dam KH, et al., 2019, Going smart, staying confused: perceptions and use of smart thermostats in British homes, Energy Research and Social Science, Vol: 57, ISSN: 2214-6296
Given the significant contribution of housing to energy consumption, research into how residents use energy-saving technologies has been gathering pace. In this study, we investigate the perception and use of domestic smart heating controls by a small group of residents in London, UK. These residents are supplied by a district heat network (DHN) through underfloor heating systems, and took part in a trial where their controls were upgraded from traditional thermostats to smart thermostats. Pre- and post-trial interviews were used to assess changes in how residents interacted with and perceived their controls and heating systems. After the upgrade, more residents were satisfied with the usability of their controls and programmed heating schedules which matched their actual occupancy patterns, but they also made ad-hoc temperature and schedule adjustments more frequently. These changes provide insight into how a unique sample of residents, “twice removed” from the most intuitive methods of heating control, adjusted their behaviour and perceptions following a technology upgrade. Although the small sample size and lack of long-term monitoring limits the generalizability of our results, the findings open avenues for further research into whether smart heating controls change user behaviour in a way that improves the predictability of heating demand, a crucial aspect of improving DHN operation and reducing related emissions.
García Kerdan I, Giarola S, Hawkes A, 2019, A novel energy systems model to explore the role of land use and reforestation in achieving carbon mitigation targets: A Brazil case study, Journal of Cleaner Production, Vol: 232, Pages: 796-821, ISSN: 0959-6526
Due to its low global share of direct energy consumption and greenhouse gas emissions (1–2%), the implications of technological transitions in the agricultural and forestry sector on the energy system have been overlooked. This paper introduces the Agriculture and Land Use Sector module part of the ModUlar energy System Environment (MUSE), a novel energy system simulation model. The study presents a generalisable method that enables energy modellers to characterise agricultural technologies within an energy system modelling framework. Different mechanisation processes were characterised to simulate intensification/extensification transitions in the sector and its wider implications in the energy and land use system aiming at providing reliable non-energy outputs similarly to those found in dedicated land use models. Additionally, a forest growth model has been integrated to explore the role of reforestation alongside decarbonisation measures in the energy system in achieving carbon mitigation pathways. To illustrate the model's capabilities, Brazil is used as case study. Outputs suggest that by 2030 under a 2 °C mitigation scenario, most of Brazil agricultural production would move from ‘transitional’ to ‘modern’ practices, improving productivity and reducing deforestation rates, at the expense of higher energy and fertiliser demand. By mid-century Brazil has the potential to liberate around 24.4 Mha of agricultural land, where large-scale reforestation could have the capacity to sequester around 5.6 GtCO2, alleviating mitigation efforts in the energy system, especially reducing carbon capture and storage technology investments in the industry and power sector.
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