152 results found
Vijay A, Hawkes A, 2018, Impact of dynamic aspects on economics of fuel cell based micro co-generation in low carbon futures, Energy, Vol: 155, Pages: 874-886, ISSN: 0360-5442
This article evaluates the impact of a range of dynamic performance parameters on the techno-economics of fuel cell based micro co-generation. The main novelties in methodology are: (1) Analysis in the context of future power system decarbonisation, (2) Use of the Long Run Marginal Cost of electricity, (3) Combination of the above with dynamic aspects such as start-up cost, ramping limit, turn down ratio, minimum up time and minimum down time and (4) Identification of sensitive parameters for future research. To this end it combines a national level energy systems model with an individual heating system model. A case study of the United Kingdom is considered for the year 2035. Economic viability of fuel cell based micro co-generation hinges upon the use of an optimized control strategy. With such a control strategy, a hot start-up approach offers much greater economic potential than a cold start-up approach. The best case ratio of maximum allowable hot standby power to the nominal value is 4.2 while the ratio for cold start is only 1.1. Combinations involving low ramping limits less than 70 W/min and limited turn down ratios above 35% need to be avoided as they seriously hinder economic performance.
Allison J, Bell K, Clarke J, et al., 2018, Assessing domestic heat storage requirements for energy flexibility over varying timescales, Applied Thermal Engineering, Vol: 136, Pages: 602-616, ISSN: 1359-4311
© 2018 The Authors This paper explores the feasibility of storing heat in an encapsulated store to support thermal load shifting over three timescales: diurnal, weekly and seasonal. A building simulation tool was used to calculate the space heating and hot water demands for four common UK housing types and a range of operating conditions. A custom sizing methodology calculated the capacities of storage required to fully meet the heat demands over the three timescales. Corresponding storage volumes were calculated for a range of heat storage materials deemed suitable for storing heat within a dwelling, either in a tank or as an integral part of the building fabric: hot water, concrete, high-temperature magnetite blocks, and a phase change material. The results indicate that with low temperature heat storage, domestic load shifting is feasible over a few days. Beyond this timescale, the very large storage volumes required make integration in dwellings problematic. Supporting load shifting over 1–2 weeks is feasible with high temperature storage. Retention of heat over periods longer than this is challenging, even with significant levels of insulation. Seasonal storage of heat in an encapsulated store appeared impractical in all cases modelled due to the volume of material required.
Jalil Vega FA, Hawkes A, 2018, Spatially resolved optimization for studying the role of hydrogen for heat decarbonization pathways, ACS Sustainable Chemistry and Engineering, Vol: 6, Pages: 5835-5842, ISSN: 2168-0485
This paper studies the economic feasibility of installing hydrogen networks for decarbonising heat in urban areas. The study uses the Heat Infrastructure and Technology (HIT) spatially-resolved optimisation model to trade-off energy supply, infrastructure and end-use technology costs for the most important heat-related energy vectors; gas, heat, electricity, and hydrogen. Two model formulations are applied to UK urban area: one with an independent hydrogen network, and one that allows for retrofitting the gas network into hydrogen. Results show that for average hydrogen price projections, cost-effective pathways for heat decarbonisation towards 2050 comprise including heat networks supplied by a combination of district level heat pumps and gas boilers in the domestic and commercial sectors, and hydrogen boilers in the domestic sector. For a low hydrogen price scenario, when retrofitting the gas network into hydrogen, a cost-effective pathway is replacing gas by hydrogen boilers in the commercial sector, and a mixture of hydrogen boilers and heat networks supplied by district level heat pumps, gas, and hydrogen boilers for the domestic sector. Compared to the first modelled year, CO2 emissions reductions of 88% are achieved by 2050. These results build on previous research on the role of hydrogen in cost-effective heat decarbonisation pathways.
Oluleye G, Hawkes AD, Allison J, et al., An optimisation study on integrating and incentivising Thermal Energy Storage (TES) in a dwelling energy system, SDEWES2017
There is an ongoing debate over future decarbonisation of gas networks using biomethane, and increasingly hydrogen, in gas network infrastructure. Some emerging research presents gas network decarbonisation options as a tractable alternative to ‘all-electric’ scenarios that use electric appliances to deliver the traditional gas services such as heating and cooking. However, there is some uncertainty as to the technical feasibility, cost and carbon emissions of gas network decarbonisation options. In response to this debate the Sustainable Gas Institute at Imperial College London has conducted a rigorous systematic review of the evidence surrounding gas network decarbonisation options. The study focuses on the technologies used to generate biomethane and hydrogen, and examines the technical potentials, economic costs and emissions associated with the full supply chains involved. The following summarises the main findings of this research. The report concludes that there are a number of options that could significantly decarbonise the gas network, and doing so would provide energy system flexibility utilising existing assets. However, these options will be more expensive than the existing gas system, and the GHG intensity of these options may vary significantly. In addition, more research is required, particularly in relation to the capabilities of existing pipework to transport hydrogen safely.
Crow DJG, Giarola S, Hawkes AD, 2018, A dynamic model of global natural gas supply, Applied Energy, Vol: 218, Pages: 452-469, ISSN: 0306-2619
This paper presents the Dynamic Upstream Gas Model (DYNAAMO); a new, global, bottom-up model of natural gas supply. In contrast to most “static” supply-side models, which bracket resources by average cost, DYNAAMO creates a range of dynamic outputs by simulating investment and operating decisions in the upstream gas industry triggered in response to investors’ expectations of future gas prices. Industrial data from thousands of gas fields is analysed and used to build production and expenditure profiles which drive the economics of supply at field level. Using these profiles, a novel methodology for estimating supply curves is developed which incorporates the size, age and operating environment of gas fields, and treats explicitly the fiscal, abandonment, exploration and emissions costs of production. The model is validated using the US shale gas boom in the 2000s as a historic case study. It is found that the modelled market share of supply by field environment replicates the observed trend during the period 2000–2010, and that the model price response during the same period – due to lower capacity margins and the financing of new projects – is consistent with market behaviour.
Giarola S, Forte O, Lanzini A, et al., 2018, Techno-economic assessment of biogas-fed solid oxide fuel cell combined heat and power system at industrial scale, Applied Energy, Vol: 211, Pages: 689-704, ISSN: 0306-2619
Wastewater treatment plants (WWTP) are currently very energy and greenhouse gas intensive processes. An important opportunity to reduce both of these quantities is via the use of biogas produced within the treatment process to generate energy. This paper studies the optimal energy and economic performance of a wastewater treatment facility fitted with a solid oxide fuel cell (SOFC) based combined heat and power (CHP) plant. An optimisation framework is formulated and then applied to determine cost, energy and emissions performance of the retrofitted system when compared with conventional alternatives.Results show that present-day capital costs of SOFC technology mean that it does not quite compete with the conventional alternatives. But, it could become interesting if implemented in thermally-optimised WWTP systems. This would increase the SOFC manufacturing volumes and drive a reduction of capital and fixed operating costs.
© 2018 Elsevier B.V. Software tools for process simulation and optimization have increasingly been used in industry to design and operate complex, highly interconnected plants. This allows the design of industrial plants to be profitable and to meet quality, safety, environmental and other standards. The aim of this work is to create a platform to simulate industrial sugarcane first generation process. Brazilian sugarcane industry is a well known process with many parameters available from industrial and literature data. The current first generation process seems to have reached the state of art and not great improvements seams to emerge nowadays. However engineering research has dedicated great efforts recently to improve efficiency through the use of industrial and agricultural residues. Most of these studies are related to the use of lignocellulosic material and vinasse. In this context an easy and simple platform has been developed to provide reliable outputs that could provide data for the studies of viability, social and environmental impacts when an additional process are interconnected to the first generation plant. The model has been validated using industrial data in order to attain the most realistic outputs.
Luh S, Budinis S, Schmidt TJ, et al., 2018, Decarbonisation of the Industrial Sector by means of Fuel Switching, Electrification and CCS, Editors: Friedl, Klemes, Radl, Varbanov, Wallek, Publisher: ELSEVIER SCIENCE BV, Pages: 1311-1316
Sechi S, Giarola S, Lanzini A, et al., 2018, An optimization method to estimate the SOFC market in waste water treatment, Editors: Friedl, Klemes, Radl, Varbanov, Wallek, Publisher: ELSEVIER SCIENCE BV, Pages: 415-420
Sachs J, Hidayat S, Giarola S, et al., 2018, The role of CCS and biomass-based processes in the refinery sector for different carbon scenarios, Editors: Friedl, Klemes, Radl, Varbanov, Wallek, Publisher: ELSEVIER SCIENCE BV, Pages: 1365-1370
Garcia Kerdan I, Hawkes AD, Giarola S, Implications of Future Natural Gas Infrastructure on Bioenergy Production, Land Use Change and Related Emissions: A Brazil Case Study, 1st SDEWES Latin America
Due to its low global share of direct energy consumption (3-5%) and greenhouse gas emissions (1-2%), energy systems models (ESM) have unfairly overlooked the implications of technological transitions in the agricultural sector. In fact, if the demand of agrochemicals and land use changes (LUC) due to expansion of bioenergy crops and increasing food demand are considered, the sector is indirectly responsible for up to 30% of global emissions. This paper introduces the Agriculture and Land Use Sector Simulation Module (Ag&LU-SM) which is integrated in a novel ESM, called MUSE, the ModUlar energy systems Simulation Environment. The Ag&LU-SM simulates the investments in agricultural energy technologies through the concept of mechanisation diffusion to meet the demand of sector’s commodities, such as crops, animal and forestry products, as well as the implications due to LUC when arable or forest land is allocated to bioenergy crops. The aim is to study the sector’s dynamics and resource competition between bioenergy and natural gas at a country level. Brazil, one of the major bioenergy producers and with large amounts of oil and natural gas reserves, is used as a case study to study the implications in terms of land use change in two different scenarios. One scenario explores a ten-fold expansion of bioenergy production by 2050, which means a 6% annual growth rate. The second scenario explores the expansion of natural gas production while halving bioenergy production (3% annual growth rate). Results show that, in order to meet the future food and bioenergy demand, the agricultural sector should move from transitional to modern agricultural practices, improve the productivity at the expense of higher energy consumption, invest in efficient agricultural practices to reduce land-related emissions and have the opportunity to liberate crop and pasture land that could be used for dedicated energy crops. Finally, the development of a gas infrastructure coul
Oluleye G, Allison J, Kelly N, et al., 2018, A Multi-period Mixed Integer Linear Program for Assessing the Benefits of Power to Heat Storage in a Dwelling Energy System, Editors: Friedl, Klemes, Radl, Varbanov, Wallek, Publisher: ELSEVIER SCIENCE BV, Pages: 1451-1456
Budinis S, Giarola S, Sachs J, et al., 2017, Modelling the impacts of investors' decision making on decarbonisation pathways in industry, 10th Annual Meeting of the IAMC, Publisher: IAMC
The Paris Climate agreement calls for dramatic changes in the energy system. This will be challenging for demand sectors like industry, which is notoriously energy intensive. Although increased efficiency has proven to be suitable options to reduce energy and environmental impacts, stringent regulations on carbon will require this sector to undergo an unprecedented innovation effort, which will go well beyond cost efficiency measures to include the deployment of novel technologies and, most likely, of carbon capture and storage (CCS).This manuscript focuses on the uptake of novel technologies in the industrial sector and the barriers which might prevent or slow down the pace of innovation. Some of these barriers are technological as they depend on the availability and the technology readiness level of a specific technology. Others are instead related to the attitude that investors show towards innovative and the inherent level of risk. Among the many innovation options in the industrial sector, the focus here is on the uptake of the carbon capture and storage technologies.The industrial sector is modelled including the top-energy intensive industries, such as those manufacturing pulp and paper, iron and steel, chemicals and petrochemicals, the non-ferrous metals as well as non-metallic minerals. The simulations are carried out using a novel energy systems model, MUSE, the Modular energy systems Simulation Environment.
Balcombe P, Brandon NP, Hawkes AD, 2017, Characterising the distribution of methane and carbon dioxide emissions from the natural gas supply chain, Journal of Cleaner Production, Vol: 172, Pages: 2019-2032, ISSN: 0959-6526
Methane and CO2 emissions from the natural gas supply chain have been shown to vary widely butthere is little understanding about the distribution of emissions across supply chain routes,processes, regions and operational practises. This study defines the distribution of total methaneand CO2 emissions from the natural gas supply chain, identifying the contribution from each stageand quantifying the effect of key parameters on emissions. The study uses recent high-resolutionemissions measurements with estimates of parameter distributions to build a probabilistic emissionsmodel for a variety of technological supply chain scenarios. The distribution of emissions resemblesa log-log-logistic distribution for most supply chain scenarios, indicating an extremely heavy tailedskew: median estimates which represent typical facilities are modest at 18 – 24 g CO2 eq./ MJ HHV,but mean estimates which account for the heavy tail are 22 – 107 g CO2 eq./ MJ HHV. To place thesevalues into context, emissions associated with natural gas combustion (e.g. for heat) areapproximately 55 g CO2/ MJ HHV. Thus, some supply chain scenarios are major contributors to totalgreenhouse gas emissions from natural gas. For methane-only emissions, median estimates are 0.8 –2.2% of total methane production, with mean emissions of 1.6 - 5.5%. The heavy tail distribution isthe signature of the disproportionately large emitting equipment known as super-emitters, whichappear at all stages of the supply chain. The study analyses the impact of different technologicaloptions and identifies a set of best technological option (BTO) scenarios. This suggests thatemissions-minimising technology can reduce supply chain emissions significantly, with this studyestimating median emissions of 0.9% of production. However, even with the emissions-minimisingtechnologies, evidence suggests that the influence of the super-emitters remains. Therefore,emissions-minimising technology is only part of the soluti
Schmidt O, Gambhir A, Staffell IL, et al., 2017, Future cost and performance of water electrolysis: An expert elicitation study, International Journal of Hydrogen Energy, Vol: 42, Pages: 30470-30492, ISSN: 0360-3199
The need for energy storage to balance intermittent and inflexible electricity supply with demand is driving interest in conversion of renewable electricity via electrolysis into a storable gas. But, high capital cost and uncertainty regarding future cost and performance improvements are barriers to investment in water electrolysis. Expert elicitations can support decision-making when data are sparse and their future development uncertain. Therefore, this study presents expert views on future capital cost, lifetime and efficiency for three electrolysis technologies: alkaline (AEC), proton exchange membrane (PEMEC) and solid oxide electrolysis cell (SOEC). Experts estimate that increased R&D funding can reduce capital costs by 0–24%, while production scale-up alone has an impact of 17–30%. System lifetimes may converge at around 60,000–90,000 h and efficiency improvements will be negligible. In addition to innovations on the cell-level, experts highlight improved production methods to automate manufacturing and produce higher quality components. Research into SOECs with lower electrode polarisation resistance or zero-gap AECs could undermine the projected dominance of PEMEC systems. This study thereby reduces barriers to investment in water electrolysis and shows how expert elicitations can help guide near-term investment, policy and research efforts to support the development of electrolysis for low-carbon energy systems.
Vijay A, Hawkes A, 2017, The techno-economics of small-scale residential heating in low carbon futures, Energies, Vol: 10, ISSN: 1996-1073
Existing studies that consider the techno-economics of residential heating systems typically focus on their performance within present-day energy systems. However, the energy system within which these technologies operate will need to change radically if climate change mitigation is to be achieved. This article addresses this problem by modelling small-scale heating techno-economics in the context of significant electricity system decarbonisation. The current electricity market price regime based on short run marginal costs is seen to provide a very weak investment signal for electricity system investors, so an electricity price regime based on long run marginal energy costs is also considered, using a case study of the UK in 2035. The economic case for conventional boilers remains stronger in most dwelling types. The exception to this is for dwellings with high annual heat demand. Sensitivity studies demonstrate the impact of factors such as price of natural gas, carbon intensity of the central grid and thermodynamic performance. Fuel cell micro combined heat and power shows most potential under the long run electricity price regime, and heat pumps under the short run electricity price regime. This difference highlights the importance of future electricity market structure on consumer choice of heating systems in the future.
Jalil-Vega F, Hawkes AD, Integrated Urban Energy Systems Approach for Assessing the Role of Hydrogen in Heat Decarbonisation Pathways: A UK Case Study, SDEWES Latin America
Guo Y, Hawkes AD, Natural Gas Game facing Low-carbon Transition: Scenarios on America Gas Exportation Strategies with Agent-based Modelling, SDEWES Latin America
Sechi S, Giarola S, Lanzini A, et al., 2017, Techno-economic assessment of the effects of biogas rate fluctuations on industrial applications of solid-oxide fuel cells, ESCAPE-27, Publisher: Elsevier, ISSN: 1570-7946
Wastewater treatment is an energy and greenhouse gas intensive process. An important opportunity to reduce both of these quantities is via the use of biogas in co-generation systems. Solid-oxide fuel cells (SOFCs) are the generator types studied in this work.The feasibility of the retrofitting of a wastewater treatment facility fitted with a SOFC combined heat and power energy provision system is assessed including effects of uncertainties in biogas availability on cost and energy performance. A two-stage stochastic optimization framework is proposed to provide feedback on the energy co-generation system design.Results quantify standard deviations in the biogas rate beyond which the SOFC capacity factor might drop below 80 % and change the optimal size of the modules to install.Keywords: solid-oxide fuel cells, stochastic optimization, wastewater treatment, biogas.
Hawkes AD, Jalil-Vega F, Modelling heat supply and infrastructure trade-offs for studying heat decarbonisation pathways in a UK case study, Tenth Annual Meeting of the IAMC
Speirs J, Balcombe P, Johnson E, et al., 2017, A Greener Gas Grid: What Are the Options?, A greener gas grid: what are the options?
Sachs J, Giarola S, Hawkes AD, 2017, Agent-based model for energy-related investment decisions in the residential building sector, International Energy Workshop, Publisher: International Energy Workshop
Giarola S, Budinis S, Sachs J, et al., 2017, Long-term decarbonisation scenarios in the industrial sector, International Energy Workshop
Decarbonisation targets will drive every sector in the energy system to rapidly adopt innovativetechnologies to achieve the dramatic emissions reductions required. Among all, sectors like in-dustry, which currently exhibit a very high energy intensity, are likely to undergo major changes.This manuscript focuses on the appraisal of the effects of a CO2tax in the investment and operationdecisions in industry. Within the larger modelling framework typical of an integrated assessmentmodel, the sector is modelled including the top-energy intensive industries, such as those man-ufacturing pulp and paper, iron and steel, chemicals and petrochemicals, the non-ferrous metalsas well as non-metallic minerals. The simulations are carried out using a novel energy systemsmodel, MUSE, the Modular Universal energy systems Simulation Environment model.
Schmidt O, Hawkes, Gambhir, et al., 2017, The future cost of electrical energy storage based on experience rates, Nature Energy, Vol: 2, ISSN: 2058-7546
Electrical energy storage could play a pivotal role in future low-carbon electricity systems, balancing inflexible or intermittentsupply with demand. Cost projections are important for understanding this role, but data are scarce and uncertain.Here, we construct experience curves to project future prices for 11 electrical energy storage technologies. We find that,regardless of technology, capital costs are on a trajectory towards US$340 ± 60 kWh−1for installed stationary systems andUS$175 ± 25 kWh−1for battery packs once 1 TWh of capacity is installed for each technology. Bottom-up assessment ofmaterial and production costs indicates this price range is not infeasible. Cumulative investments of US$175–510 billion wouldbe needed for any technology to reach 1 TWh deployment, which could be achieved by 2027–2040 based on market growthprojections. Finally, we explore how the derived rates of future cost reduction influence when storage becomes economicallycompetitive in transport and residential applications. Thus, our experience-curve data set removes a barrier for further studyby industry, policymakers and academics.
Jalil Vega F, Hawkes AD, 2017, Spatially resolved model for studying decarbonisation pathways for heat supply and infrastructure trade-offs, Applied Energy, Vol: 210, Pages: 1051-1072, ISSN: 1872-9118
Heat decarbonisation is one of the main challenges of energy system decarbonisation. However, existing energy planning models struggle to compare heat decarbonisation approaches because they rarely capture trade-offs between heat supply, end-use technologies and network infrastructure at sufficient spatial resolution. A new optimisation model is presented that addresses this by including trade-offs between gas, electricity, and heat infrastructure, together with related supply and end-use technologies, with high spatial granularity. The model is applied in case studies for the UK. For the case modelled it is shown that electrification of heat is most cost-effective via district level heat pumps that supply heat networks, instead of individual building heat pumps. This is because the cost of reinforcing the electricity grid for installing individual heat pumps does not sufficiently offset heat infrastructure costs. This demonstrates the importance of considering infrastructure trade-offs. When modelling the utilisation of a decarbonised gas, the penetration of heat networks and location of district level heat supply technologies was shown to be dependent on linear heat density and on zone topology. This shows the importance of spatial aspects. Scenario-specific linear heat density thresholds for heat network penetration were identified. For the base case, penetration of high temperature heat networks was over 50% and 60% by 2050 for linear heat densities over 1500 and 2500 kWh/m. For the case when medium heat temperature networks were additionally available, a mix of both networks was observed. Medium temperature heat network penetration was over 20%, 30%, and 40% for linear heat densities of over 1500, 2500, and 3000 kWh/m, while high temperature heat network penetration was over 20% and 30% for linear heat densities of under 2000 and 1500 kWh/m respectively.
Chávez-Rodríguez MF, Dias L, Simoes S, et al., 2017, Modelling the natural gas dynamics in the Southern Cone of Latin America, Applied Energy, Vol: 201, Pages: 219-239, ISSN: 1872-9118
Natural gas plays an important role in the Southern cone energy system, and is expected to increase in primary supply in the future. This paper presents a new energy systems model for the Southern Cone region of Latin America, covering five regions (Argentina, Bolivia, South and Centre Chile, North Chile, and Brazil) with the aim to explore, up to 2030, the interplay between (i) the expected consumption of natural gas for electricity generation and end-use consumption (i.e. residential, commercial, transport and industry) in each country, (ii) the inter- and intra-country potential role as producer and consumer of natural gas, and (iii) the possible supply network of LNG and natural gas via pipeline and domestic production. It is found that, under a Constrained Investment Scenario, the gross domestic gas production of the Southern Cone from 2012 to 2030 could be 62 Tcf, whereas under an Unconstrained Scenario, it could rise to 75 Tcf. This highlights the economic potential of the unconventional gas resources of Argentina and projections of associated gas from the Campos and Santos basins in Brazil. However, accessing these resources poses financial challenges. Nonetheless, results clearly indicate significant potential for an increase in regional natural gas trade in the Southern Cone.
Vijay A, Fouquet N, Staffell IL, et al., 2017, The value of electricity and reserve services in low carbon electricity systems, Applied Energy, Vol: 201, Pages: 111-123, ISSN: 1872-9118
Decarbonising electricity systems is essential for mitigating climate change. Future systems will likely incorporate higher penetrations of intermittent renewable and inflexible nuclear power. This will significantly impact on system operations, particularly the requirements for flexibility in terms of reserves and the cost of such services. This paper estimates the interrelated changes in wholesale electricity and reserve prices using two novel methods. Firstly, it simulates the short run marginal cost of generation using a unit commitment model with post-processing to achieve realistic prices. It also introduces a new reserve price model, which mimics actual operation by first calculating the day ahead schedules and then letting deviations from schedule drive reserve prices. The UK is used as a case study to compare these models with traditional methods from the literature. The model gives good agreement with and historic prices in 2015. In a 2035 scenario, increased renewables penetration reduces mean electricity prices, and leads to price spikes due to expensive plants being brought online briefly to cope with net load variations. Contrary to views previously held in literature, a renewable intensive scenario does not lead to a higher reserve price than a fossil fuel intensive scenario. Demand response technology is shown to offer sizeable economic benefits when maintaining system balance. More broadly, this framework can be used to evaluate the economics of providing reserve services by aggregating decentralised energy resources such as heat pumps, micro-CHP and electric vehicles.
Bosch J, Staffell, Hawkes AD, 2017, Temporally-explicit and spatially-resolved global onshore wind energy potentials, Energy, Vol: 131, Pages: 207-217, ISSN: 0360-5442
Several influential energy systems models indicate that renewable energy must provide a significant share of the world's electricity to limit global temperature rises to below 2 °C this century. To better represent the costs and other implications of this shift, it is important that these models realistically characterise the technical and economic potential of renewable energy technologies. Towards this goal, this paper presents the first temporally-explicit Geospatial Information System (GIS) methodology to characterise the global onshore wind energy potential with respect to topographical features, land use and environmental constraints. The approach combines the hourly NASA MERRA-2 global wind speed data set with the spatially-resolved DTU Global Wind Atlas. This yields high resolution global capacity factors for onshore wind, binned into seasonal and diurnal time-slices to capture the important temporal variability. For each country, the wind power generation capacity available for various capacity factor ranges is produced, and made freely available to the community. This data set can be used to assess the economically viable wind energy potential on a global or per-country basis, and as an input to various energy systems models.
Gambhir A, Napp T, Hawkes A, et al., 2017, The contribution of non-CO2 greenhouse gas mitigation to achieving long-term temperature goals, Energies, Vol: 10, ISSN: 1996-1073
This paper analyses the emissions and cost impacts of mitigation of non-CO2 greenhouse gases (GHGs) at a global level, in scenarios aimed at meeting a range of long-term temperature goals (LTTGs). The study combines an integrated assessment model (TIAM-Grantham) representing CO2 emissions (and their mitigation) from the fossil fuel combustion and industrial sectors, coupled with a model covering non-CO2 emissions (GAINS), using the latest global warming potentials from the Intergovernmental Panel on Climate Change’s Fifth Assessment Report. We illustrate that in general non-CO2 mitigation measures are less costly than CO2 mitigation measures, with the majority of their abatement potential achievable at US2005$100/tCO2e or less throughout the 21st century (compared to a marginal CO2 mitigation cost which is already greater than this by 2030 in the most stringent mitigation scenario). As a result, the total cumulative discounted cost over the period 2010–2100 (at a 5% discount rate) of limiting global average temperature change to 2.5 °C by 2100 is $48 trillion (about 1.6% of cumulative discounted GDP over the period 2010–2100) if only CO2 from the fossil fuel and industrial sectors is targeted, whereas the cost falls to $17 trillion (0.6% of GDP) by including non-CO2 GHG mitigation in the portfolio of options—a cost reduction of about 65%. The criticality of non-CO2 mitigation recommends further research, given its relatively less well-explored nature when compared to CO2 mitigation.
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