Publications
215 results found
Dubey L, Cooper J, Hawkes A, 2023, Minimum detection limits of the TROPOMI satellite sensor across North America and their implications for measuring oil and gas methane emissions, Science of the Total Environment, Vol: 872, Pages: 1-9, ISSN: 0048-9697
Methane emissions from natural gas are of ever-increasing importance as we struggle to reach Paris climate targets. Locating and measuring emissions from natural gas can be particularly difficult as they are often widely distributed across supply chains. Satellites are increasingly used to measure these emissions, with some such as TROPOMI giving daily coverage worldwide, making locating and quantifying these emissions easier. However, there is little understanding of the real-world detection limits of TROPOMI, which can cause emissions to go undetected or be misattributed. This paper uses TROPOMI and meteorological data to calculate, and create a map of, the minimum detection limits of the TROPOMI satellite sensor across North America for different campaign lengths. We then compared these to emission inventories to determine the quantity of emissions that can be captured by TROPOMI. We find that minimum detection limits vary from 500-8800 kg/h/pixel in a single overpass to 50-1200 kg/h/pixel for a yearlong campaign. This leads to 0.04 % of a year's emissions being captured in a single (day) measurement to 14.4 % in a 1-year measurement campaign. Assuming gas sites contain super-emitters, emissions of between 4.5 % - 10.1 % from a single measurement and 35.6 % - 41.1 % for a yearlong campaign are captured.
Dubey L, Cooper J, Staffell I, et al., 2023, Comparing satellite methane measurements to inventory estimates: A Canadian case study, ATMOSPHERIC ENVIRONMENT-X, Vol: 17
Stettler MEJ, Woo M, Ainalis D, et al., 2022, Review of Well-to-Wheel lifecycle emissions of liquefied natural gas heavy goods vehicles, APPLIED ENERGY, Vol: 333, ISSN: 0306-2619
de Ven D-JV, Mittal S, Gambhir A, et al., 2022, A multi-model analysis of post-Glasgow climate action and feasibility gap
<jats:title>Abstract</jats:title> <jats:p>The COP26 Glasgow process resulted in many countries strengthening their 2030 emissions reduction targets and announcing net-zero pledges for 2050–2070. We use four diverse integrated assessment models (IAMs) to assess CO<jats:sub>2</jats:sub> emission trajectories in the near- and long-term based on national policies and pledges, combined with a non-CO<jats:sub>2</jats:sub> infilling model and a simple climate model to assess the temperature implications of such trajectories. Critically, we also consider the feasibility of national long-term pledges towards net-zero, to understand where the challenges to achieving them could lie. Whilst near-term pledges alone lead to warming above 2°C, the addition of long-term pledges leads to emissions trajectories compatible with a well-below 2°C future, across all four IAMs. However, whilst IAM heterogeneity translates to diverse decarbonisation pathways towards long-term targets, all modelled pathways indicate several feasibility concerns, relating to the cost of mitigation, as well as to rates and scales of deployed technologies and measures.</jats:p>
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).
Bakkaloglu S, Cooper J, Hawkes A, 2022, Life cycle environmental impact assessment of methane emissions from the biowaste management strategy of the United Kingdom: Towards net zero emissions, JOURNAL OF CLEANER PRODUCTION, Vol: 376, ISSN: 0959-6526
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Parkinson B, Balcombe P, Speirs JF, et al., 2022, Levelized cost of CO2 mitigation from hydrogen production routes (vol 12, pg 19, 2019), ENERGY & ENVIRONMENTAL SCIENCE, ISSN: 1754-5692
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.
Mulugetta Y, Sokona Y, Trotter PA, et al., 2022, Africa needs context-relevant evidence to shape its clean energy future, NATURE ENERGY, Vol: 7, Pages: 1015-1022, ISSN: 2058-7546
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Cooper J, Hawkes A, 2022, Cutting emissions outside borders, Nature Climate Change, Vol: 12, Pages: 965-966, ISSN: 1758-678X
Cooper J, Dubey L, Bakkaloglu S, et al., 2022, Hydrogen emissions from the hydrogen value chain-emissions profile and impact to global warming, Science of the Total Environment, Vol: 830, ISSN: 0048-9697
Future energy systems could rely on hydrogen (H2) to achieve decarbonisation and net-zero goals. In a similar energy landscape to natural gas, H2 emissions occur along the supply chain. It has been studied how current gas infrastructure can support H2, but there is little known about how H2 emissions affect global warming as an indirect greenhouse gas. In this work, we have estimated for the first time the potential emission profiles (g CO2eq/MJ H2,HHV) of H2 supply chains, and found that the emission rates of H2 from H2 supply chains and methane from natural gas supply are comparable, but the impact on global warming is much lower based on current estimates. This study also demonstrates the critical importance of establishing mobile H2 emission monitoring and reducing the uncertainty of short-lived H2 climate forcing so as to clearly address H2 emissions for net-zero strategies.
Cooper J, Dubey L, Hawkes A, 2022, The life cycle environmental impacts of negative emission technologies in North America, Sustainable Production and Consumption, Vol: 32, Pages: 880-894, ISSN: 2352-5509
Negative emission technologies (NETs) could play a key role in ensuring net-zero and longer-term net negative emission ambitions are met. However, greenhouse gas emissions (and other pollutants) will occur over the life cycle of a NET and will need to be taken into consideration when developing schemes to roll out their use. We compare five NETs: afforestation/reforestation (AR), enhanced weathering (EW), mangrove restoration (MR), bioenergy and direct air capture with carbon storage (BECCS and DAC), using life cycle assessment to determine their environmental impacts (global warming, freshwater, toxicity etc.). We find that there is a wide range in the environmental impacts estimated across the NETs and the context in which they are used will directly impact which NET has low or high environmental impacts. This is an important aspect to consider when deciding which NET to prioritise in strategies to roll out their use on large scales. If consistent removal of CO2 from the atmosphere is the goal, then AR and MR have the lowest environmental impacts. However, if large and quick CO2 removal is the goal then EW, DAC and BECCS have similar, if not lower, environmental impacts.
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.
Bakkaloglu S, Cooper J, Hawkes A, 2022, Methane emissions along biomethane and biogas supply chains are underestimated, One Earth, Vol: 5, Pages: 724-736, ISSN: 2590-3322
Although natural gas generates lower CO2 emissions, gas extraction, processing, and distribution all release methane, which has a greater global warming potential than CO2. Biomethane and biogas that use organic wastes as a feedstock have emerged as alternatives to natural gas, with lower carbon and methane emissions. However, the extent to which methane is still emitted at various stages along biogas and biomethane supply chains remains unclear. Here, we adopt a Monte Carlo approach to systematically synthesize the distribution of methane emissions at each key biomethane and biogas supply chain stage using data collected from the existing literature. We show that the top 5% of emitters are responsible for 62% of emissions. Methane emissions could be more than two times of greater than previously estimated, with the digestate handling stage responsible for the majority of methane released. To ensure the climate benefits of biomethane and biogas production, effective methane-mitigation strategies must be designed and deployed at each supply chain stage.
Cooper J, Dubey L, Hawkes A, 2022, Life cycle assessment of negative emission technologies for effectiveness in carbon sequestration, 29th CIRP Life Cycle Engineering Conference, Publisher: Elsevier, Pages: 357-361, ISSN: 2212-8271
As climate change and emissions targets tighten, negative emissions technologies (NETs) will play a crucial role in making sure global temperature rises do not exceed Paris Agreement goals. There are a variety of NETs that can be used to abate greenhouse gas (GHG) emissions, but it is uncertain which are more effective, and by how much, as well as what the net GHG removal is as all NETs will emit GHGs and other pollutants throughout their life cycles. We conducted a life cycle assessment (LCA) to compare four NETs: afforestation/reforestation, enhanced weathering, direct air capture and bioenergy with carbon capture and storage. These are compared on their life cycle impacts to climate change, land use change and toxicity (human and terrestrial). We find that the most effective NET is afforestation/reforestation for the environmental impacts considered while enhanced weathering and direct air capture are less effective. However, when the rate of carbon removal is considered, we find that afforestation/reforestation is much slower than the other NETs. Therefore, while it has the lowest impacts to the environment, either long time frames or large-scale implementation is needed for it to match the capacity of direct air capture or bioenergy with carbon capture and storage.
Edelenbosch OY, Miu L, Sachs J, et al., 2022, Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework, iScience, Vol: 25
Decarbonizing the building sector depends on choices made at the household level, which are heterogeneous. Agent-based models are tools used to describe heterogeneous choices but require data-intensive calibration. This study analyzes a novel, cross-country European household-level survey, including sociodemographic characteristics, energy-saving habits, energy-saving investments, and metered household electricity consumption, to enhance the empirical grounding of an agent-based residential energy choice model. Applying cluster analysis to the data shows that energy consumption is not straightforwardly explained by sociodemographic classes, preferences, or attitudes, but some patterns emerge. Income consistently has the largest effect on demand, dwelling efficiency, and energy-saving investments, and the potential to improve a dwellings' energy use affects the efficiency investments made. Including the various sources of heterogeneity found to characterize the model agents affects the timing and speed of the transition. The results reinforce the need for grounding agent-based models in empirical data, to better understand energy transition dynamics.
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
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.
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.
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.
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.
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.
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