Publications
230 results found
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
Mascarenhas KL, Malvezzi S, Hawkes AD, et al., 2022, University-industry-government partnership working on sustainable development goals in Brazil, International Journal of Intellectual Property Management, Vol: 12, Pages: 42-63, ISSN: 1478-9647
This paper aims to provide insights into the capabilities of a university of working cooperatively with the industry and the government, to promote the sustainable development goals (SDGs) and foster the United Nations 2030 Agenda. Through the case study of a Brazilian research centre, structured in a triple helix model (university-industry-government), the potential of this tripartite partnership is explored in the context of long-term timeframe research. The contribution of the research centre towards the SDGs is analysed through its main activities. It suggests that information and dissemination of knowledge about the impacts generated by research, business, policy and behaviour are fundamental means to kindle a new mentality aligned with the SDGs. Therefore, it indicates that the triple helix model may boost a faster and more efficient trajectory that embraces a broad spectrum from research to implementation, which enables more feasible contributions to the SDG targets.
Yliruka MI, Moret S, Jalil-Vega F, et al., 2022, The Trade-Off between Spatial Resolution and Uncertainty in Energy System Modelling, Computer Aided Chemical Engineering, Pages: 2035-2040
In energy system models, computational tractability is often maintained by adopting a simplified temporal and spatial representation in a deterministic model formulation i.e., neglecting uncertainty. However, such simplifications have been shown to impact the optimal result. To address the question of how to prioritize the limited computational resources, the trade-off between spatial resolution and uncertainty is assessed by applying a novel method based on global sensitivity analysis to a peer-reviewed heat decarbonization model. For all output variables apart from the total system and fuel cost, spatial resolution is ranks amongst the five most important model inputs. It is the most relevant factor for investment decisions on network capacities. For the total fuel consumption and emissions, spatial resolution turns out to be more relevant than the fuel prices themselves. Compared across all outputs, the analysis suggests the impact of spatial resolution is comparable the impact of heat demand levels and the discount rate.
Wickham D, Hawkes A, Jalil-Vega F, 2022, Hydrogen supply chain optimisation for the transport sector – Focus on hydrogen purity and purification requirements, Applied Energy, Vol: 305, Pages: 1-48, ISSN: 0306-2619
This study presents a spatially-resolved optimisation model to assess cost optimal configurations of hydrogen supply chains for the transport sector up to 2050. The model includes hydrogen grades and separation/purification technologies, offering the possibility to assess the effects that hydrogen grades play in the development of cost-effective hydrogen supply chains, including the decisions to repurpose gas distribution networks or blending hydrogen into them. The model is implemented in a case study of Great Britain, for a set of decarbonisation and learning rate scenarios. A base case with a medium carbon price scenario shows that the total discounted cost of the hydrogen supply chain is significantly higher than shown in previous studies, largely due to the additional costs from purification/separation needed to meet hydrogen purity standards for transport applications. Furthermore, it was shown that producing hydrogen from steam methane reforming with carbon capture and storage; installing new transmission pipelines; repurposing the gas distribution network to supply 100% hydrogen; and purifying hydrogen with a pressure swing adsorption system locally at the refuelling station; is a cost optimal configuration for the given technoeconomic assumptions, providing hydrogen at £6.18 per kg at the pump. Purification technologies were found to contribute to 14% and 30% of total discounted investment and operation costs respectively, highlighting the importance of explicitly including them into hydrogen supply chain models for the transport sector.
Rai U, Oluleye G, Hawkes A, 2022, An optimisation model to determine the capacity of a distributed energy resource to contract with a balancing services aggregator, Applied Energy, Vol: 306, Pages: 1-22, ISSN: 0306-2619
Electricity systems require a real-time balance between generation and demand for electricity. In the past, changing the output of larger generators has been the primary means of achieving this balance, but more recently, smaller distributed energy resources (DERs) are becoming a contributor. As electricity generation becomes more intermittent due to the uptake of renewables, the task of balancing the electricity system is becoming more challenging. As such, there will be a greater need for DERs for grid balancing in future. DERs may be delivered via aggregators for this purpose, where several individual resources are grouped to be traded in contracts with a System Operator (SO). This paper presents a novel framework for DERs aggregators to determine by optimisation the capacity of a generating unit to contract with the SO, using mixed integer non-linear programming (MINLP). Results show the site revenue increases between 6.2% and 29.8% compared to the heuristic approach previously employed. Sensitivity analysis is performed to assess the impact of temporal resolution of demand characterisation on results, showing that increased resolution improves accuracy significantly, and reduces the estimate of capacity that the site should contract with the aggregator.
Machado PG, Hawkes A, Ribeiro CDO, 2021, What is the future potential of CCS in Brazil? An expert elicitation study on the role of CCS in the country, International Journal of Greenhouse Gas Control, Vol: 112, Pages: 1-11, ISSN: 1750-5836
This article presents the results of an expert elicitation about the role of carbon capture and storage (CCS) in Brazil as a measure to reduce greenhouse gases emissions, its costs, and the most appropriate policies to develop this technology at a commercial scale. Experts were elicited based on a scenario oriented towards net-zero emissions in Brazil by 2050. Five parameters were elicited, and all present great uncertainty. Results show that experts believe CCS has the potential to reduce CO2 emissions in Brazil. Still, with the current lack of supporting market, policy and regulatory frameworks in place, it could take another five years to begin implementation, reaching commercial scale not earlier than 12 years from the time of writing. Experts say that the chance of Brazil reaching the elicited value of 190 million tons of CO2 per year is very low. This indicates that though CCS can play a role in achieving net-zero emissions in the country, many other measures will be necessary. Policy-wise, the experts bet on a carbon market as the most probable policy instrument to help CCS development in Brazil. The experts also estimated the total investment necessary to reach 190 million tons of CO2 per year captured at USD 58 billion. When it comes to public expenditures, experts believe the role of the government in funding CCS in the country would be approximately 25% of total investments coming from different sources of public investment.
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.
Cooper J, Dubey L, Hawkes A, 2021, Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting, Environmental Science: Atmospheres, Vol: 2, Pages: 9-23, ISSN: 2634-3606
Oil and gas activities are a major source of methane and in recent years multiple companies have made pledges to cut their emissions of this potent greenhouse gas. Satellites are a promising technology, but their relevance to emissions reconciliation and reporting has not yet been independently established. In this review paper, we assess the capabilities of satellites to determine their role in emissions detection, reconciling and reporting in the upstream section of the oil and gas value chain. In reconciling, satellites have a role in verifying emissions estimated by other technologies, as well as in determining what is causing discrepancies in emission estimates. There are many limitations to satellite usage which need to be addressed before their widescale or routine use by the sector, particularly relating to where they can be used, and high uncertainty associated with their emission estimates. However, where limitations are overcome, satellites could potentially transform the way emissions are reconciled and reported through long-term monitoring, building emission profiles, and tracking whether emission targets are being met. Satellites are valuable tools, not just to the oil and gas sector but to international governments and organisations, as abating methane is crucial for achieving Paris Agreement ambitions.
Grant N, Hawkes A, Napp T, et al., 2021, Cost reductions in renewables can substantially erode the value of carbon capture and storage in mitigation pathways, One Earth, Vol: 4, Pages: 1588-1601, ISSN: 2590-3322
Tackling climate change requires a rapid transition to net-zero energy systems. A variety of different technologies could contribute to this transition, and uncertainty remains over their relative role and value. A growing school of thought argues that rapid cost reductions in renewables reduce the need for carbon capture and storage (CCS) in mitigation pathways. Here we use an integrated assessment model to explore how the value of CCS is affected by cost reductions in solar photovoltaics, onshore, and offshore wind. Low-cost renewables could erode the value of CCS by 15%–96% across different energy sectors. Renewables directly compete with CCS, accelerate power sector decarbonization, and enable greater electrification of end-use sectors. CCS has greatest value and resilience to low-cost renewables in sustainable bioenergy/industrial applications, with limited value in hydrogen/electricity generation. This suggests that targeted, rather than blanket, CCS deployment represents the best strategy for achieving the Paris Agreement goals.
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.
Cooper J, Balcombe P, Hawkes A, 2021, The quantification of methane emissions and assessment of emissions data for the largest natural gas supply chains, Journal of Cleaner Production, Vol: 320, Pages: 1-10, ISSN: 0959-6526
Methane emitted from natural gas supply chains are a major source of greenhouse gas emissions, but there is uncertainty on the magnitude of emissions, how they vary, and which key factors influence emissions. This study estimates the variation in emissions across the major natural gas supply chains, alongside an estimate of uncertainty which helps identify the areas at the greatest emissions ‘risk’. Based on the data, we estimate that 26.4 Mt CH4 (14.5–48.2 Mt CH4) was emitted by these supply chains in 2017. The risk assessment identified a significant proportion of countries to be at high risk of high emissions. However, there is a large dependency on Tier 1 emission factors, inferring a high degree of uncertainty and a risk of inaccurate emission accounting. When emissions are recalculated omitting Tier 1 data, emissions reduce by 47% to 3.8-fold, downstream and upstream respectively, across regions. More efforts in collecting robust and transparent primary data should be made, particularly in Non-Annex 1 countries, to improve our understanding of methane emissions.
Grant N, Hawkes A, Mittal S, et al., 2021, The policy implications of an uncertain carbon dioxide removal potential, Joule, Vol: 5, Pages: 2593-2605, ISSN: 2542-4351
Many low-carbon scenarios rely on carbon dioxide removal (CDR) to meet decarbonization goals. The feasibility of large-scale CDR deployment is highly uncertain, and existing scenarios have been criticized for overreliance on CDR. We conduct an expert survey on the feasible potential for CDR via bioenergy with carbon capture and storage, direct air capture and afforestation. We use the survey results to represent uncertainty in future CDR availability and explore the implications in an integrated assessment model. Stochastic optimization demonstrates that uncertainty in future CDR availability provides a strong rationale to increase near-term rates of decarbonization. In scenarios with high CDR uncertainty, emissions are reduced by an additional 10 GtCO2e in 2030 compared with scenarios with no consideration of CDR uncertainty. This highlights the urgent need to increase ambition contained in nationally determined contributions (NDCs) for 2030, to get the world on track to deliver 1.5°C and to hedge against an uncertain future CDR potential.
Ludlow J, Jalil-Vega F, Rivera XS, et al., 2021, Organic waste to energy: Resource potential and barriers to uptake in Chile, SUSTAINABLE PRODUCTION AND CONSUMPTION, Vol: 28, Pages: 1522-1537, ISSN: 2352-5509
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, Vol: 16, ISSN: 1748-9326
Carbon dioxide removal (CDR) features heavily in low-carbon scenarios, where it often substitutes for emission reductions in both the near-term and long-term, enabling temperature targets to be met at lower cost. There are major concerns around the scale of CDR deployment in many low-carbon scenarios, and the risk that anticipated future CDR could dilute incentives to reduce emissions now, a phenomenon known as mitigation deterrence. Here we conduct an in-depth analysis into the relationship between emissions reduction and emissions removal in a global integrated assessment model. We explore the impact of CDR on low-carbon scenarios, illustrating how the pathway for the 2020s is highly sensitive to assumptions around CDR availability. Using stochastic optimisation, we demonstrate that accounting for uncertainty in future CDR deployment provides a strong rationale to increase rates of mitigation in the 2020s. A 20% chance of CDR deployment failure requires additional emissions reduction in 2030 of 3–17 GtCO2. Finally, we introduce new scenarios which demonstrate the risks of mitigation deterrence and the benefits of formally separating CDR and emissions reduction as climate strategies. Continual mitigation deterrence across the time-horizon leads to the temperature goals being breached by 0.2–0.3 °C. If CDR is treated as additional to emissions reduction, up to an additional 700–800 GtCO2 can be removed from the atmosphere by 2100, reducing end-of-century warming by up to 0.5 °C. This could put sub-1.5 °C targets within reach but requires that CDR is additional to, rather than replaces, emission reductions.
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.
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.
Weinstein M, Almulla Y, Vijay A, et al., 2021, Technoeconomic energy system data for modeling of India and the GCC countries
<jats:title>Abstract</jats:title> <jats:p>India has seen rapid increases in GDP, energy access, and population in recent decades, more than doubling its overall energy consumption since 2000. Meanwhile, India produces approximately 70% of its electricity from coal. With electricity demand only projected to grow in the coming years, the Government of India has pledged to install 450 GW of renewable energy by 2030. The Gulf Cooperation Council (GCC) countries[1], meanwhile, have comparatively small populations with excellent renewable energy resources, particularly solar. The ability to trade power between these two regions could potentially provide India with a highly reliable carbon-free power source. At the same time, it can motivate the shift to low carbon economy in the GCC and add a new market for its solar power. The provided data in this article relate to the current makeup of the energy systems of both regions, renewable resource potentials, and projections of future demand. The data have been compiled from numerous sources, mainly government and international agencies.<jats:sup>[1] </jats:sup>GCC countries are Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates</jats:p>
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.
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