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  • Journal article
    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.

  • Journal article
    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, 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.

  • Journal article
    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.

  • Journal article
    Kell AJM, McGough AS, Forshaw M, 2021,

    The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets

    , Sustainable Computing: Informatics and Systems, Vol: 30, Pages: 1-12, ISSN: 2210-5379

    Electricity supply must be matched with demand at all times. This helps reduce the chances of issues such as load frequency control and the chances of electricity blackouts. To gain a better understanding of the load that is likely to be required over the next 24h, estimations under uncertainty are needed. This is especially difficult in a decentralized electricity market with many micro-producers which are not under central control.In this paper, we investigate the impact of eleven offline learning and five online learning algorithms to predict the electricity demand profile over the next 24h. We achieve this through integration within the long-term agent-based model, ElecSim. Through the prediction of electricity demand profile over the next 24h, we can simulate the predictions made for a day-ahead market. Once we have made these predictions, we sample from the residual distributions and perturb the electricity market demand using the simulation, ElecSim. This enables us to understand the impact of errors on the long-term dynamics of a decentralized electricity market.We show we can reduce the mean absolute error by 30% using an online algorithm when compared to the best offline algorithm, whilst reducing the required tendered national grid reserve required. This reduction in national grid reserves leads to savings in costs and emissions. We also show that large errors in prediction accuracy have a disproportionate error on investments made over a 17-year time frame, as well as electricity mix.

  • Journal article
    Bakkaloglu S, Lowry D, Fisher R, France J, Brunner D, Chen H, Nisbet Eet al., 2021,

    Quantification of methane emissions from UK biogas plants

    , Waste Management, Vol: 124, Pages: 82-93, ISSN: 0956-053X

    The rising number of operational biogas plants in the UK brings a new emissions category to consider for methane monitoring, quantification and reduction. Minimising methane losses from biogas plants to the atmosphere is critical not only because of their contribution of methane to global warming but also with respect to the sustainability of renewable energy production. Mobile greenhouse gas surveys were conducted to detect plumes of methane emissions from the biogas plants in southern England that varied in their size, waste feed input materials and biogas utilization. Gaussian plume modelling was used to estimate total emissions of methane from ten biogas plants based on repeat passes through the plumes. Methane emission rates ranged from 0.1 to 58.7 kg CH4 hr-1, and the percentage of losses relative to the calculated production rate varied between 0.02 and 8.1%. The average emission rate was 15.9 kg CH4 hr-1, and the average loss was 3.7%. In general, methane emission rates from smaller farm biogas plants were higher than from larger food waste biogas plants. We also suggest that biogas methane emissions may account for between 0.4 and 3.8%, with an average being 1.9% of the total methane emissions in the UK excluding the sewage sludge biogas plants.

  • Journal article
    Sechi S, Giarola S, Lanzini A, Gandiglio M, Santarelli M, Oluleye G, Hawkes Aet 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.

  • Journal article
    Nikas A, Gambhir A, Trutnevyte E, Koasidis K, Lund H, Thellufsen JZ, Mayer D, Zachmann G, Miguel LJ, Ferreras-Alonso N, Sognnaes I, Peters GP, Colombo E, Howells M, Hawkes A, van den Broek M, Van de Ven DJ, Gonzalez-Eguino M, Flamos A, Doukas Het 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.

  • Journal article
    Oluleye G, Gandiglio M, Santarelli M, Hawkes Aet 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.

  • Journal article
    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.

  • Journal article
    Budinis S, Sachs J, Giarola S, Hawkes Aet 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.

  • Journal article
    Moya D, Budinis S, Giarola S, Hawkes Aet 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).

  • Report
    Speirs J, Jalil-Vega F, Cooper J, Gerber Machado P, Giarola S, Brandon N, Hawkes Aet 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.

  • Journal article
    Grant N, Hawkes A, Napp T, Gambhir Aet 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.

  • Journal article
    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.

  • Journal article
    Lyrio de Oliveira L, García Kerdan I, de Oliveira Ribeiro C, Oller do Nascimento CA, Rego EE, Giarola S, Hawkes Aet 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.

  • Journal article
    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.

  • Journal article
    Luh S, Budinis S, Giarola S, Schmidt TJ, Hawkes Aet 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.

  • Conference paper
    Kell AJM, Forshaw M, McGough AS, 2020,

    Exploring market power using deep reinforcement learning for intelligent bidding strategies

    , 8th IEEE International Conference on Big Data (Big Data), Publisher: IEEE, Pages: 4402-4411, ISSN: 2639-1589
  • Journal article
    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.

  • Journal article
    García Kerdan I, Jalil-Vega F, Toole J, Gulati S, Giarola S, Hawkes Aet 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.

  • Journal article
    García Kerdan I, Giarola S, Jalil-Vega F, Hawkes Aet al., 2019,

    Carbon sequestration potential from large-scale reforestation and sugarcane expansion on abandoned agricultural lands in Brazil

    , Polytechnica, Vol: 2, Pages: 9-25, ISSN: 2520-8497

    Since 1850, over 145 ± 16 PgC (μ ± 1σ) has been emitted worldwide due to land-use change and deforestation. Besides industrial carbon capture and storage (CCS), storing carbon in forestry products and in regenerated forest has been recognized as a cost-effective carbon sequestration option, with an estimated worldwide sink potential of about 50–100 PgC (15–36 PgC from tropical forest alone). This paper proposes the expansion of a Brazilian integrated assessment model (MUSE-Brazil) by integrating a non-spatial biomass-growth model. The aim is to account for carbon sequestration potential from either reforestation or sugarcane expansion in abandoned agricultural lands. Modelling outputs suggest that Brazil has the potential to liberate up to 32.3 Mha of agricultural land by 2035, reaching 68.4 Mha by mid-century. If a sugarcane expansion policy is promoted, by 2050, the largest sequestration rates would come from above and below ground biomass pools; gradually releasing to the atmosphere around 1.6 PgC or 1.2% of the current Brazilian land carbon stock due to lower SOC carbon pools when turning agricultural lands into sugarcane crops. On the other hand, a reforestation-only scenario projects that by 2035 the baseline year carbon stock could be recovered and by 2050 the country’s carbon stock would have been increased by 3.2 PgC, reaching annual net sequestration rates of 0.1 PgC y−1, mainly supported by natural vegetation regeneration in the Cerrado biome.

  • Journal article
    Miu LM, Mazur CM, Van Dam KH, Lambert RSC, Hawkes A, Shah Net 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.

  • Journal article
    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.

  • Journal article
    Sachs J, Moya D, Giarola S, Hawkes Aet al., 2019,

    Clustered spatially and temporally resolved global heat and cooling energy demand in the residential sector

    , Applied Energy, Vol: 250, Pages: 48-62, ISSN: 0306-2619

    Climatic conditions, population density, geography, and settlement structure all have a strong influence on the heating and cooling demand of a country, and thus on resulting energy use and greenhouse gas emissions. In particular, the choice of heating or cooling system is influenced by available energy distribution infrastructure, where the cost of such infrastructure is strongly related to the spatial density of the demand. As such, a better estimation of the spatial and temporal distribution of demand is desirable to enhance the accuracy of technology assessment. This paper presents a Geographical Information System methodology combining the hourly NASA MERRA-2 global temperature dataset with spatially resolved population data and national energy balances to determine global high-resolution heat and cooling energy density maps. A set of energy density bands is then produced for each country using K-means clustering. Finally, demand profiles representing diurnal and seasonal variations in each band are derived to capture the temporal variability. The resulting dataset for 165 countries, published alongside this article, is designed to be integrated into a new integrated assessment model called MUSE (ModUlar energy systems Simulation Environment)but can be used in any national heat or cooling technology analysis. These demand profiles are key inputs for energy planning as they describe demand density and its fluctuations via a consistent method for every country where data is available.

  • Journal article
    Realmonte G, Hawkes A, Gambhir A, Tavoni M, Glynn J, Koberle A, Drouet Let al., 2019,

    An inter-model assessment of the role of direct air capture in deep mitigation pathways

    , Nature Communications, Vol: 10, ISSN: 2041-1723

    The feasibility of large-scale biological CO2 removal to achieve stringent climate targets remains unclear. Direct Air CarbonCapture and Storage (DACCS) offers an alternative negative emissions technology (NET) option. Here we conduct the firstinter-model comparison on the role of DACCS in 1.5 and 2°C scenarios, under a variety of techno-economic assumptions.Deploying DACCS significantly reduces mitigation costs, and it complements rather than substitutes other NETs. The key factorlimiting DACCS deployment is the rate at which it can be scaled up. Our scenarios’ average DACCS scale-up rates of 1.5GtCO2/yr would require considerable sorbent production and up to 300 EJ/yr of energy input by 2100. The risk of assumingthat DACCS can be deployed at scale, and finding it to be subsequently unavailable, leads to a global temperature overshoot ofup to 0.8°C. DACCS should therefore be developed and deployed alongside, rather than instead of, other mitigation options.

  • Journal article
    Cooper J, Balcombe P, Hawkes A, 2019,

    Life cycle environmental impacts of natural gas drivetrains used in UK road freighting and impacts to UK emission targets

    , Science of the Total Environment, Vol: 674, Pages: 482-493, ISSN: 0048-9697

    Using natural gas as a fuel in the road freight sector instead of diesel could cut greenhouse gas and air quality emissions but the switch alone is not enough to meet UK climate targets. A life cycle assessment (LCA) has been conducted comparing natural gas trucks to diesel, biodiesel, dimethyl ether and electric trucks on impacts to climate change, land use change, air quality, human health and resource depletion. This is the first LCA to consider a full suite of environmental impacts and is the first study to estimate what impact natural gas could have on reducing emissions form the UK freight sector. If LNG is used, climate change impacts could be up to 33% lower per km and up to 12% lower per kWh engine output. However, methane emissions will eliminate any benefits if they exceed 1.5–3.5% of throughput for typical fuel consumption. For non-climate impacts, natural gas exhibits lower emissions (11–66%) than diesel for all indicators. Thus, for natural gas climate benefits are modest. However, emissions of CO, methane and particulate matter are over air quality limits set for UK trucks. Of the other options, electric and biodiesel trucks perform best in climate change, but are the worst with respect to land use change (which could have significant impacts on overall climate change benefits), air quality, human toxicity and metals depletion indicators. Natural gas could help reduce the sector's emissions but deeper decarbonization options are required to meet 2030 climate targets, thus the window for beneficial utilisation is short.

  • Journal article
    Crow DJG, Balcombe P, Brandon N, Hawkes ADet al., 2019,

    Assessing the impact of future greenhouse gas emissions from natural gas production

    , Science of the Total Environment, Vol: 668, Pages: 1242-1258, ISSN: 0048-9697

    Greenhouse gases (GHGs) produced by the extraction of natural gas are an important contributor to lifecycle emissions and account for a significant fraction of anthropogenic methane emissions in the USA. The timing as well as the magnitude of these emissions matters, as the short term climate warming impact of methane is up to 120 times that of CO 2 . This study uses estimates of CO 2 and methane emissions associated with different upstream operations to build a deterministic model of GHG emissions from conventional and unconventional gas fields as a function of time. By combining these emissions with a dynamic, techno-economic model of gas supply we assess their potential impact on the value of different types of project and identify stranded resources in various carbon price scenarios. We focus in particular on the effects of different emission metrics for methane, using the global warming potential (GWP) and the global temperature potential (GTP), with both fixed 20-year and 100-year CO 2 -equivalent values and in a time-dependent way based on a target year for climate stabilisation. We report a strong time dependence of emissions over the lifecycle of a typical field, and find that bringing forward the stabilisation year dramatically increases the importance of the methane contribution to these emissions. Using a commercial database of the remaining reserves of individual projects, we use our model to quantify future emissions resulting from the extraction of current US non-associated reserves. A carbon price of at least 400 USD/tonne CO 2 is effective in reducing cumulative GHGs by 30–60%, indicating that decarbonising the upstream component of the natural gas supply chain is achievable using carbon prices similar to those needed to decarbonise the energy system as a whole. Surprisingly, for large carbon prices, the choice of emission metric does not have a significant impact on cumulative emissions.

  • Journal article
    García Kerdan I, Morillón Gálvez D, Sousa G, Suárez de la Fuente S, Silva R, Hawkes Aet al., 2019,

    Thermodynamic and thermal comfort optimisation of a coastal social house considering the influence of the thermal breeze

    , Building and Environment, Vol: 155, Pages: 224-246, ISSN: 0360-1323

    Tropical coastal areas are characterised by high levels of wind and solar resources with large potentials to be utilised for low-energy building design. This paper presents a multi-objective optimisation framework capable of evaluating cost-efficient and low-exergy coastal building designs considering the influence of the thermal breeze. An integrated dynamic simulation tool has been enhanced to consider the impacts of the sea-land breeze effect, aiming at potentiating natural cross-ventilation to improve occupant's thermal comfort and reduce cooling energy demand. Furthermore, the technological database considers a wide range of active and passive energy conservation measures. As a case study, a two-storey/two-flat detached social house located in the North-Pacific coast of Mexico has been investigated. The optimisation problem has considered the minimisation of: i. annual exergy consumption, ii. life cycle cost, and iii. thermal discomfort. Optimisation results have shown that adequate building orientation and window opening control to optimise the effects of the thermal breeze, combined with other passive and active strategies such as solar shading devices, an improved envelope's physical characteristics, and solar assisted air source heat pumps have provided the best performance under a limited budget. Compared to the baseline design, the closest to utopia design has increased thermal comfort by 93.8% and reduced exergy consumption by 10.3% whilst increasing the life cycle cost over the next 50 years by 18.5% (from US$39,864 to US$47,246). The importance of renewable generation incentives is further discussed as a counter effect measure for capital cost increase as well as unlocking currently high-cost low-exergy technologies.

  • Journal article
    Cooper J, Balcombe P, 2019,

    Life cycle environmental impacts of natural gas drivetrains used in road freighting

    , Procedia CIRP, Vol: 80, Pages: 334-339, ISSN: 2212-8271
  • Journal article
    Napp TA, Few S, Sood A, Bernie D, Hawkes A, Gambhir Aet al., 2019,

    The role of advanced demand-sector technologies and energy demand reduction in achieving ambitious carbon budgets

    , Applied Energy, Vol: 238, Pages: 351-367, ISSN: 0306-2619

    Limiting cumulative carbon emissions to keep global temperature increase to well below 2 °C (and as low as 1.5 °C) is an extremely challenging task, requiring rapid reduction in the carbon intensity of all sectors of the economy and with limited leeway for residual emissions. Addressing residual emissions in ‘challenging-to-decarbonise’ sectors such as the industrial and aviation sectors relies on the development and commercialization of innovative advanced technologies, currently still in their infancy. The aim of this study was to (a) explore the role of advanced technologies in achieving deep decarbonisation of the energy system and (b) provide technology-specific details of how rapid and deep carbon intensity reductions can be achieved in the energy demand sectors. This was done using TIAM-Grantham – a linear cost optimization model of the global energy system with a detailed representation of demand-side technologies. We find that the inclusion of advanced technologies in the demand sectors, together with energy demand reduction through behavioural changes, enables the model to achieve the rapid and deep decarbonisation of the energy system associated with limiting global warming to below 2 °C whilst at the same time reduces reliance on negative emissions technologies by up to ∼18% compared to the same scenario with a standard set of technologies. Realising such advanced technologies at commercial scales, as well as achieving such significant reductions in energy demand, represents a major challenge for policy makers, businesses and civil society. There is an urgent need for continued R&D efforts in the demand sectors to ensure that advanced technologies become commercially available when we need them and to avoid the gamble of overreliance on negative emissions technologies to offset residual emissions.

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