74 results found
van de Ven DJ, Mittal S, Gambhir A, et al., 2023, A multimodel analysis of post-Glasgow climate targets and feasibility challenges, Nature Climate Change, ISSN: 1758-678X
The COP26 Glasgow process resulted in many countries strengthening their 2030 emissions reduction targets and announcing net-zero pledges for 2050–2070 but it is not clear how this would impact future warming. Here, we use four diverse integrated assessment models (IAMs) to assess CO2 emission trajectories in the near- and long-term on the basis of national policies and pledges, combined with a non-CO2 infilling model and a simple climate model to assess the temperature implications. We also consider the feasibility of national long-term pledges towards net-zero. While near-term pledges alone lead to warming above 2 °C, the addition of long-term pledges leads to emissions trajectories compatible with a future well below 2 °C, across all four IAMs. However, while IAM heterogeneity translates to diverse decarbonization pathways towards long-term targets, all modelled pathways indicate several feasibility concerns, relating to the cost of mitigation and the rates and scales of deployed technologies and measures.
Philip S, Kell A, Giarola S, et al., 2022, Transport decarbonisation in the UK: an agent-based modelling study
Kell A, Giarola S, Hawkes A, 2022, An investigation of the impact of bounded rationality on the decarbonisation of Kenya's power system, Fourteenth IAMC Annual Meeting 2021
How can we transition to a low-carbon energy supply to limit the effects of climate change?The methodology of quantitative energy models can have an impact on the advice inferred. We compare Kenya’s electricity system transition to 2050 with a 2-model inter-comparison. To explore the uncertainty, we use an agent-based simulation model (MUSE) and an optimisation model (OSeMOSYS).
Sechi S, Giarola S, Leone P, 2022, Taxonomy for Industrial Cluster Decarbonization: An Analysis for the Italian Hard-to-Abate Industry, ENERGIES, Vol: 15
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Giarola S, Sachs J, d'Avezac M, et al., 2022, MUSE: An open-source agent-based integrated assessment modelling framework, Energy Strategy Reviews, Vol: 44, Pages: 1-21, ISSN: 2211-467X
Integrated assessment models (IAMs) are a cornerstone of an effective approach toclimate change mitigation. Despite the variety of methodologies for characterisingthe energy system, land use change, economics, and climate response, the modellingcommunity has an open and urgent request for tools capable of more realistic interpretation of the energy transition, capturing human behaviour, and embodying theprinciples of transparency, reproducibility, and flexibility of use.This paper presents an open-source modelling framework designed to fill thatgap. Named MUSE (ModUlar energy systems Simulation Environment), this newagent-based model supports flexible characterisation of agent decision-making, including individual goals, bounded-rationality, imperfect foresight, and limited knowledge during the decision process. MUSE integrates this agent-based approach in apartial-equilibrium framework and enables a technology-rich description of the energy systems with an unprecedented degree of flexibility for including technological,temporal, and geographical granularity. The structure of MUSE creates the abilityto produce climate change mitigation assessments that are more grounded, and moretangible model outputs for conceiving effective approaches to mitigation. MUSE isavailable open source under a GNU General Public License v3.0 on GitHub at thislink https://github.com/SGIModel/MUSE_OS.
van de Ven D-J, Nikas A, Koasidis K, et al., 2022, COVID-19 recovery packages can benefit climate targets and clean energy jobs, but scale of impacts and optimal investment portfolios differ among major economies, One Earth, Vol: 5, Pages: 1042-1054, ISSN: 2590-3322
To meet the Paris temperature targets and recover from the effects of the pandemic, many countries have launched economic recovery plans, including specific elements to promote clean energy technologies and green jobs. However, how to successfully manage investment portfolios of green recovery packages to optimize both climate mitigation and employment benefits remains unclear. Here, we use three energy-economic models, combined with a portfolio analysis approach, to find optimal low-carbon technology subsidy combinations in six major emitting regions: Canada, China, the European Union (EU), India, Japan, and the United States (US). We find that, although numerical estimates differ given different model structures, results consistently show that a >50% investment in solar photovoltaics is more likely to enable CO2 emissions reduction and green jobs, particularly in the EU and China. Our study illustrates the importance of strategically managing investment portfolios in recovery packages to enable optimal outcomes and foster a post-pandemic green economy.
Moya D, Copara D, Borja A, et al., 2022, Geospatial and temporal estimation of climatic, end-use demands, and socioeconomic drivers of energy consumption in the residential sector in Ecuador, Energy Conversion and Management, Vol: 261, Pages: 115629-115629, ISSN: 0196-8904
It is widely acknowledged that the drivers for energy consumption in the residential sector are ambient temperature, energy demand, population density, and socio-economic conditions. However, there are no studies in the literature assessing the temporal and spatial distribution of these drivers for a region or country. The decision-making process of the energy transition will be enhanced by using geospatial-resolved and temporal-explicit energy consumption drivers. This study estimates the climatic, end-use demands, and socio-economic drivers of energy consumption in the residential sector of Ecuador at a high spatio-temporal resolution between 2010 and 2020. This research uses publicly available datasets to calculate seven energy consumption drivers in the residential sector of Ecuador: (1) calibrated gridded population density at 1 km2 resolution; (2) validated gridded space heating demand at 1 km2 resolution; (3) validated gridded space cooling demand at 1 km2 resolution; (4) validated gridded water heating demand at 1 km2 resolution; (5) calibrated gridded gross domestic product at 1 km2 resolution; (6) calibrated gridded gross domestic product per capita at 1 km2 resolution; and (7) calibrated regional human development index, at city level. Disaggregation of the drivers at a high spatial resolution for the entire country in a range of 10 years was considered. The final high-1 km2 resolution results can be used for the evaluation of different energy policies in terms of long-term planning and in techno-economic modelling of energy systems and decarbonisation pathways.
Panoutsou C, Giarola S, Ibrahim D, et al., 2022, Opportunities for low indirect land use biomass for biofuels in Europe, Applied Sciences-Basel, Vol: 12, ISSN: 2076-3417
Sustainable biofuels are an important tool for the decarbonisation of transport. This is especially true in aviation, maritime, and heavy-duty sectors with limited short-term alternatives. Their use by conventional transport fleets requires few changes to the existing infrastructure and engines, and thus their integration can be smooth and relatively rapid. Provision of feedstock should comply with sustainability principles for (i) producing additional biomass without distorting food and feed markets and (ii) addressing challenges for ecosystem services, including biodiversity, and soil quality. This paper performs a meta-analysis of current research for low indirect land use change (ILUC) risk biomass crops for sustainable biofuels that benefited either from improved agricultural practices or from cultivation in unused, abandoned, or severely degraded land. Two categories of biomass crops are considered here: oil and lignocellulosic. The findings confirm that there are significant opportunities to cultivate these crops in European agro-ecological zones with sustainable agronomic practices both in farming land and in land with natural constraints (unused, abandoned, and degraded land). These could produce additional low environmental impact feedstocks for biofuels and deliver economic benefits to farmers
Sesini M, Giarola S, Hawkes AD, 2022, Solidarity measures: Assessment of strategic gas storage on EU regional risk groups natural gas supply resilience, Applied Energy, Vol: 308, Pages: 1-15, ISSN: 0306-2619
This paper focuses on strategic storage as a solidarity measure in response to short-term “high-impact, low-probability” (HILP) disruptions in the European Union (EU) gas supply from major suppliers (i.e., Ukraine, Russia, Norway, and North Africa), assuming its implementation in selected Member States. A two-stage stochastic cost minimization gas transport model is used to evaluate the impact of HILP events on the level of demand curtailment, survival time, and the natural gas supply mix of EU regional risk group. Results show that geographic proximity alone, without solidarity measures, is inadequate in providing system resilience. In contrast, solidarity measures lead to a longer survival time for regional risk groups (14 days) and to a reduction in system (15%) and LNG (70%) costs relative to a base scenario with no strategic storage. The analysis stresses the value of the coordinated use of strategic storage in balancing the natural gas network during emergencies, and provides further evidence supporting the EU legislative path towards an Energy Union.
Moya D, Giarola S, Hawkes A, 2022, Geospatial Big Data analytics to model the long-term sustainable transition of residential heating worldwide, 2021 IEEE International Conference on Big Data (Big Data), Publisher: IEEE, Pages: 4035-4046
Geospatial big data analytics has received much attention in recent years for the assessment of energy data. Globally, spatial datasets relevant to the energy field are growing rapidly every year. This research has analysed large gridded datasets of outdoor temperature, end-use energy demand, end-use energy density, population and Gros Domestic Product to end with usable inputs for energy models. These measures have been recognised as a means of informing infrastructure investment decisions with a view to reaching sustainable transition of the residential sector. However, existing assessments are currently limited by a lack of data clarifying the spatio-temporal variations within end-use energy demand. This paper presents a novel Geographical Information Systems (GIS)-based methodology that uses existing GIS data to spatially and temporally assess the global energy demands in the residential sector with an emphasis on space heating. Here, we have implemented an Unsupervised Machine Learning (UML)-based approach to assess large raster datasets of 165 countries, covering 99.6% of worldwide energy users. The UML approach defines lower and upper limits (thresholds) for each raster by applying GIS-based clustering techniques. This is done by binning global high-resolution maps into re-classified raster data according to the same characteristics defined by the thresholds to estimate intranational zones with a range of attributes. The spatial attributes arise from the spatial intersection of re-classified layers. In the new zones, the energy demand is estimated, so-called energy demand zones (EDZs), capturing complexity and heterogeneity of the residential sector. EDZs are then used in energy systems modelling to assess a sustainable scenario for the long-term transition of space heating technology and it is compared with a reference scenario. This long-term heating transition is spatially resolved in zones with a range of spatial characteristics to enhance the assessment
Sognnaes I, Gambhir A, van de Ven D-J, et al., 2021, A multi-model analysis of long-term emissions and warming implications of current mitigation efforts, Nature Climate Change, Vol: 11, Pages: 1055-1062, ISSN: 1758-678X
Most of the integrated assessment modelling literature focuses on cost-effective pathways towards given temperature goals. Conversely, using seven diverse integrated assessment models, we project global energy CO2 emissions trajectories on the basis of near-term mitigation efforts and two assumptions on how these efforts continue post-2030. Despite finding a wide range of emissions by 2050, nearly all the scenarios have median warming of less than 3 °C in 2100. However, the most optimistic scenario is still insufficient to limit global warming to 2 °C. We furthermore highlight key modelling choices inherent to projecting where emissions are headed. First, emissions are more sensitive to the choice of integrated assessment model than to the assumed mitigation effort, highlighting the importance of heterogeneous model intercomparisons. Differences across models reflect diversity in baseline assumptions and impacts of near-term mitigation efforts. Second, the common practice of using economy-wide carbon prices to represent policy exaggerates carbon capture and storage use compared with explicitly modelling policies.
Sesini M, Giarola S, Hawkes AD, 2021, Strategic natural gas storage coordination among EU member states in response to disruption in the trans Austria gas pipeline: A stochastic approach to solidarity, Energy, Vol: 235, Pages: 1-13, ISSN: 0360-5442
The 2019 EU energy security agenda has led to the concept of solidarity: a coordinated response of Member States to “high-impact, low-probability” events jeopardizing the EU energy supply. At the core of this paper is a modeling analysis of storage as a non-market-based solidarity measure (the so-called strategic storage) considering whether it could be economically desirable to secure gas supply in case of disruption to the EU network. A two-stage stochastic cost minimization gas transport model was developed to study the short-term resilience of the network to supply shocks, such as a natural gas pipeline rupture, and the cost effective system response, in terms of transmission of gas flows, capacity use, and storage utilization in an interconnected gas system, taken the EU as a reference. Relative to a base scenario with no strategic storage, results show that gas import loss up to 80% on multiple different pipelines could lead to a +76% in total costs when no coordinated strategic storage is in place, compared with a −30% in total cost and a −60% in liquefied natural gas cost, when in use, emphasizing the cost-effectiveness achieved with strategic storage in securing energy to the system in emergency.
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.
Nikas A, Elia A, Boitier B, et al., 2021, Where is the EU headed given its current climate policy? A stakeholder-driven model inter-comparison., Science of the Total Environment, Vol: 793, Pages: 148549-148549, ISSN: 0048-9697
Recent calls to do climate policy research with, rather than for, stakeholders have been answered in non-modelling science. Notwithstanding progress in modelling literature, however, very little of the scenario space traces back to what stakeholders are ultimately concerned about. With a suite of eleven integrated assessment, energy system and sectoral models, we carry out a model inter-comparison for the EU, the scenario logic and research questions of which have been formulated based on stakeholders' concerns. The output of this process is a scenario framework exploring where the region is headed rather than how to achieve its goals, extrapolating its current policy efforts into the future. We find that Europe is currently on track to overperforming its pre-2020 40% target yet far from its newest ambition of 55% emissions cuts by 2030, as well as looking at a 1.0-2.35 GtCO2 emissions range in 2050. Aside from the importance of transport electrification, deployment levels of carbon capture and storage are found intertwined with deeper emissions cuts and with hydrogen diffusion, with most hydrogen produced post-2040 being blue. Finally, the multi-model exercise has highlighted benefits from deeper decarbonisation in terms of energy security and jobs, and moderate to high renewables-dominated investment needs.
Doukas H, Spiliotis E, Jafari MA, et al., 2021, Low-cost emissions cuts in container shipping: thinking inside the box, Transportation Research Part D: Transport and Environment, Vol: 94, ISSN: 1361-9209
Container shipping has become an emission-intensive industry; existing regulations, however, continue to display limitations. Technical emissions reduction measures require large, long-term investments, while operational measures may negatively impact transportation costs and supply-chain practices. For container shipping to become more sustainable, innovative, low-cost technological solutions are required. This study discusses such a technological game-changer which utilizes a lighter container type that, contrary to conventional ones, does not require wood in its floor. In this regard, emissions reductions are achieved both due to lower fuel consumption and tree savings. We estimate the global impact of this technology until 2050 using an integrated assessment model and considering different projections about future characteristics of the container fleet. Our results indicate that the adoption of the examined technology can reduce emissions by 4.7–18.8% depending on the main fuel used in container shipping lines, saving also a total of about 44 million trees.
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.
Brown M, Siddiqui S, Avraam C, et al., 2021, North American energy system responses to natural gas price shocks, Energy Policy, Vol: 149, Pages: 1-11, ISSN: 0301-4215
As of 2020, North American natural gas extraction and use in the electricity sector have both reached all-time highs. The combination of North America's increased reliance on natural gas with a potential disruption to the natural gas market has several energy security implications. Additionally, policymakers interested in economic resiliency will find this study's results useful for informing the implications of the energy sectors' long-term planning and investment decisions. This paper evaluates how both the electricity and natural gas sectors could respond to hypothetical gas price shocks under different system configurations. We impose unforeseen natural gas price shocks under reference and alternative configurations resulting from a renewable generation mandate or variations to renewable capacity costs. Results from several different models are presented for the electricity and natural gas sectors separately for Canada, Mexico, and the United States. Generally, the US becomes more (less) reliant on electricity imports from Canada given a high (low) gas price shock but increases (decreases) exports to Mexico. The renewable mandate is demonstrated to buffer electricity price increases under high price shocks but price reductions under the low price shocks are dampened given less flexibility to take advantage of the low-priced natural gas. The United States is demonstrated to reduce natural gas production and net exports with high natural gas price shocks given a reduction in demand.
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.
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.
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.
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.
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.
Speirs J, Balcombe P, Blomerus P, et al., 2020, Natural gas fuel and greenhouse gas emissions in trucks and ships, Progress in Energy, Vol: 2, Pages: 012002-012002
Panteli A, Giarola S, Shah N, 2020, Strategic Biorefining Supply Chain Design for Novel Products in Immature Markets, Editors: Pierucci, Manenti, Bozzano, Manca, Publisher: ELSEVIER SCIENCE BV, Pages: 1579-1584
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.
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