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Review of existing emissions pathways and evaluation of decarbonisation rates June 2014 Authors: Olivier Dessens1, Gabrial Anandarajah1, and Ajay Gambhir2. 1 UCL Energy Institute 2 Grantham Institute, Imperial College London Version: 1.0 Reference: AVOID 2 WPC1 Funded by This work was supported by AVOID 2 programme (DECC) under contract reference no. 1104872 For more information about the AVOID 2 programme visit www.avoid.uk.net 2 Executive Summary This report presents an assessment of recent studies examining greenhouse gas (GHG) emission pathways that are compatible with limiting average global temperature rise to levels close to 2°C or at least below 2.5°C by 2100. Whilst the studies examined show some variation due to differing underlying assumptions in areas such as technology constraints and socioeconomic factors, strong commonalities could be found between the studies and the following key conclusions drawn. 1. Mitigation to 2°C or below is still possible. In order to meet stringent climate targets compatible with the 2°C goal it is necessary to limit atmospheric CO2-eq concentrations to between 450-500 parts per million by the end of the 21st Century. However, this level of climate mitigation will require a significant transformation in the way we produce and consume energy and the way we use the natural environment. In most studies examined, remaining below the 2°C target required net global emissions in 2100 to be zero or negative. This therefore required relying on technologies such as biomass with carbon capture and sequestration in order to counterbalance the unavoidable GHG emissions resulting from continued economic activity. 2. Mitigation to 2.5°C is easier to achieve. Achieving the less ambitious goal of 2.5°C typically requires limiting CO2-eq concentrations to under 550 ppm by the end of the century. However, whilst this level of mitigation may be easier to achieve, it will still require strong GHG emissions reductions typically to less than half the present day. 3. Removing key technologies will make mitigation more difficult and/or more costly. It was found that in order to remain under the 2°C target early action and a full portfolio of low-carbon technologies is needed in order to keep global mitigation costs down. Therefore the availability, cost and future performance of key technologies has an important role in achieving climate targets. Widespread electrification of the energy end use sectors combined with strong decarbonisation of electricity production occur in most mitigation scenarios. Nonfossil energy sources replace coal in the near term and gas in the medium and longterm in the electricity sector. Renewable electricity generation deployment is not by itself sufficient to achieve the required levels of electricity decarbonisation, and most of the 2°C scenarios also depend, during the second-half of the century, on the largescale deployment of CO2 capture technologies. Finally energy demand reduction can significantly reduce mitigation costs as well as the reliance on carbon capture and storage (CCS); unfortunately the demand side 3 technologies are usually studied and characterised with less detail than the supply side in the studies reviewed in this paper. 4. Delaying emission reductions will increase the need for negative emission technologies. The more delayed the start of robust mitigation policies for a specific climate goal, the higher the rate of emissions reduction after policy is implemented, and the more likely there is to be a heavy reliance on negative emissions technologies to keep within the cumulative carbon budget for the 21st century that is required to meet the climate policy. 5. Mitigation costs increase when climate targets are more stringent and when action is delayed. Costs of mitigation vary largely between models; however, in most of the scenarios, the more stringent the climate target, the higher the mitigation costs. Consumption losses for the least cost pathways to reach the 2°C target in 2100, with the assumption that all mitigation technologies are available (including all major renewables, nuclear and CCS), are in the range of 2 to 6% in 2050 and 3 to 11% in 2100 relative to the no mitigation (or “business as usual”/baseline) scenarios. Delayed action, in general, increases the global mitigation costs and also leads to a possible fossil fuel lock-in of the electricity system, creating large and expensive unusable assets. As such the most cost-effective scenarios to achieve the 2°C target are characterised by early mitigation creating clear signals for low-carbon technology investments and a near term peak in emissions (with the latest possible peaking dates occurring between 2025 and 2030, and with peak GHG emissions in the range of 30 to 50 GtCO2-eq). 6. There is scope for further analysis on the implications of mitigation scenarios. There are a number of areas where there is variation between (or a lack of transparency around assumptions for) the models used. These include: differing assumptions on population and economic growth; a lack of detail on technology costs and deployment constraints; a lack of detailed analysis of technologies and measures to achieve energy efficiency and reduced end-use demand; a lack of detail on the implications of lock-in and the consequences of early retirements of carbon-intensive technologies; and a lack of monetisation of mitigation co-benefits such as energy security and reduced air pollution. These model limitations and variations imply that there remains a detailed research agenda going forward, to help better understand the real-world drivers and constraints behind the feasibility of deep emissions reduction scenarios. 4 Table of contents 1 Introduction ................................................................................. 6 2 Studies included in the report ...................................................... 7 3 Pathways description .................................................................11 4 Socio-economic assessment ......................................................18 5 Technology parameters ..............................................................19 6 Mitigation policies .......................................................................24 7 Technology and cost implications ...............................................26 8 Co-benefits and secondary impacts of mitigation options ...........34 9 Current knowledge and data gaps ..............................................36 10 Concluding points .......................................................................38 11 References .................................................................................39 5 1. Introduction In March 1994 the UNFCCC entered into force and recognised that it is necessary to stabilize atmospheric greenhouse gas (GHG) concentrations at a level that would prevent dangerous anthropogenic interference with the climate system [1]. Defining the dangerous level is a value judgement; however a consensus between stakeholders in Copenhagen in 2009 [2] concluded that to comply with this goal the warming achieved should be limited to below 2°C compared with preindustrial times. The 2°C target is still included in the text adopted in the 2011 UNFCCC in Durban [3] as well as an assessment of scenarios that could achieve a possible temperature change below 1.5°C. To limit the long-term temperature rise to this level, deep cuts in global GHG emissions are needed. There has been a great deal of analysis to consider whether the mitigation commitments (or ‘Copenhagen pledges’) made to date are consistent with achieving a 50:50 chance of limiting the surface temperature rise to 2°C (UNEP objective [4]) with the conclusion that the scenarios including these near term pledges are not least-cost optimal pathways [5]. Many authors argue that with further ambitious global policies, the target is reachable ([6]; [7]; [8]), although others suggest it could be too late, as we are already locked into a fossil based energy system under the weaker-than-optimal “Copenhagen pledges” ([9]; [10]; [11]). Part of the reason for this dichotomy of views is that the complexity of the climate system, as well as the extent of uncertainties embedded in it, gives rise to a wide variety of possible emission trajectories that are consistent with a 2°C temperature rise. The additional uncertainties and complexities with modelling the global energy system lead to an even wider range of views on whether, or how, such cuts in emissions are possible. In this report we present an assessment of studies examining the latest GHG emission pathways that are compatible with limiting average global temperature rise to levels close to 2°C or at least below 2.5°C by the end of the 21st century. The majority of mitigation scenarios assessed over recent years have focused on GHG pathways broadly consistent with achieving atmospheric concentrations of GHGs between 450 ppm and 550 ppm. Although, as already discussed, there remains uncertainty in the relationship between atmospheric GHG concentrations and long-term temperature changes, broadly speaking the 450 scenarios are aimed at achieving an even or better chance of limiting surface warming to 2°C, and the 550 scenarios to 2.5°C. In the analysis part of this report we first examine the global pathways for greenhouse gas emissions and the subsequent rate of reduction in annual emissions to comply with targeted temperature rise below the 2°C and 2.5°C limit with at least 50% achievement chance (more likely than not). Second, we examine the changes in technologies deployment and costs between different mitigation options, focussing in particular on the implied rates of deployment of a number of key electricity decarbonisation technologies. Third, we assess if there are co-benefits reported from the mitigation and technology choices within the pathways description. Finally the last chapter outlines the perceived gaps in data and knowledge that need more scrutiny. 6 2. Studies included in the report Modelling studies and inter-model comparisons Energy Modelling Forum 27 Study (EMF27); https://emf.stanford.edu/projects/emf-27-globalmodel-comparison-exercise The 18 Integrated Assessment Models (IAMs 1) participating in EMF27 are: GCAM, FARM, MERGE, Phoenix, EC-IAM, TIAM-WORLD, IMACLIM, IMAGE, MESSAGE, POLES, REMIND, WITCH, AIM-Enduse, BET, DNE21+, GRAPE, GCAM-IIM, and ENV-Linkages. (See Table 1). This study incorporates different levels of climate policy, including a 550 and 450 ppm target. The 550 ppm target does not allow overshooting this level of CO2e concentrations at any time until 2100 whereas in the 450 ppm case a temporary overshoot is allowed before reaching the target in 2100 [12]. The study also considers two alternative policy regimes, one fragmented policy case and a scenario based on the broadly defined goal articulated in recent years by leaders in the G8 (now G7) [13]. Low climate IMpact scenarios and the Implications of required Tight emission control Strategies (LIMITS); http://www.feem-project.net/limits/ LIMITS is funded under the EU FP 7 research program and compares seven IAMs (MESSAGE, IMAGE, TIAM-ECN, REMIND, WITCH, AIM, GCAM – See table 1) over 12 scenarios. The scenario design encompasses atmospheric GHG concentrations reaching a maximum of 450 or 500 ppm (two different scenarios), the assumed level of ambition in 2020 (a reference policy reflecting the unconditional Copenhagen Pledges and a more stringent version based on conditional Copenhagen Pledges [14]), and the burden sharing scheme to be adopted once the international treaty is signed (no sharing, per capita convergence and equal effort in term of mitigation costs relative to economic output). Assessment of Climate Change Mitigation Pathways and Evaluation of the Robustness of Mitigation Cost Estimates (AMPERE); http://ampere-project.eu Ampere encompasses 12 global IAMs: REMIND, MESSAGE-MACRO, WITCH, MERGEETL, IMACLIM, IMAGE/TIMER, POLES, {GEM-E3, WorldScan, AIM-Enduse, DNE21+, GCAM scenarios until 2050 only} (See Table 1). Ampere has a strong focus on EU technology and policy and concentrates its analyses on what action over the next 2 decades implies for subsequent action to meet a 2°C goal. Following a path based on extrapolation of the current international emission reduction commitments throughout the rest of the century, model calculations suggest that global mean temperature would increase by 3.2 – 3.8°C by 2100[15] and [16]. Global Energy Assessment (GEA): Toward a Sustainable Future [17] GEA uses two integrated assessment models (MESSAGE and IMAGE) in order to analyse 60 alternative transitions pathways towards a low-carbon future. The final GEA report examines the major global challenges and their linkages to energy, the technologies and 1 In assessment of climate change, IAM refers to a mathematical tool that considers the social and economic factors that drive the emission of greenhouse gases, the biogeochemical cycles and atmospheric chemistry that determines the fate of those emissions, and the resultant effect of greenhouse gas emissions on climate, ecosystems and human welfare. 7 resources available for providing adequate, modern and affordable forms of energy, the plausible structure of future energy systems most suited to addressing the century’s challenges, and the policies and measures needed. The Roadmaps towards Sustainable Energy futures (RoSE); http://www.rose-project.org The Roadmaps towards Sustainable Energy futures (RoSE) project aims to provide a robust picture on energy sector transformation scenarios for reaching ambitious climate targets involving 5 leading integrated assessment modelling teams (using REMIND, GCAM, WITCH, IPAC, and China MARKAL). RoSE assesses the feasibility and costs of climate mitigation goals across different models, different policy regimes, and different reference assumptions [18]. The scenarios and policies within RoSE that are currently available and published are similar to the AMPERE ones; however in the future RoSE will perform more scenarios with the same climate policies (450 and 550 ppm) under different socio-economic global development (different GDP, population growth, and fossil fuels prices for example). One RoSE publication analyses the near-term role of fossil fuel usage under “late action” regarding the potential carbon-intensive electricity generation capacity that will have to be left idle when decarbonisation occurs [19]. TIAM-UCL global modelling studies: The CCC report [20] and UKERC Global study [21] In these studies the TIAM-UCL energy system IAM, using a simple climate module, simulates GHG pathways consistent with 2°C, 2.5°C and 3°C targets (with and without overshoot). Technology availability such as carbon capture and sequestration (CCS) or bioenergy with carbon capture and storage (BECCS) as well as different CO2 emission rate of reduction limits have been applied to the scenarios. The targets feasibility is discussed and technology development and system costs are reported. Assessment reports Climate Change 2014, Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [22] The IPCC assessment report builds upon more than 800 GHG emissions scenarios extracted from pre-published material in peer reviewed literature, with a large number of the most recent scenarios made up of the EMF 27, Ampere, RoSE and LIMITS studies already described. The scenarios are collated in the AR5 scenario database (IAMC AR5 Scenario Database, [23]). The scenarios are grouped into baseline scenarios and GHG mitigation scenarios, which in turn are further grouped by levels of ambition to reduce GHG emissions: the most stringent mitigation scenarios (category 1) correspond to long-term total radiative forcing targets of 2.3 to 2.9 Wm-2 (425 to 475 ppm CO2e), which are compatible with limiting global average temperature change to below 2°C. Category 2 scenarios correspond to stabilization of total radiative forcing between 2.9-3.4 Wm-2, category 3: 3.4-3.9 Wm-2, category 4: 3.9-5.1 Wm-2, and category 5: 5.1-6.8 Wm-2. Per category, the indicative temperature change ranges are between 1.7-2.2°C, 2.0-2.5°C, 2.3-3.0°C, and 3.0-4.0°C respectively. Scenarios in the highest category (Category 6) correspond to modest mitigation efforts leading to radiative forcing levels greater than 6.8 Wm-2 with temperature outcomes in 2100 above 4°C. The AR5 report also presents the implications, in terms of GHG emissions and temperature change in 2100, of the Representative Concentration Pathways (RCPs) 8 which were developed by the Integrated Assessment Modelling (IAM) community to provide a standardised set of GHG pathways. These RCPs are also summarised in this paper. The UNEP Emissions Gap Report 2012 [4] For this assessment, the analyses of 12 research and/or modelling groups have been reviewed (Peterson Institute for International Economics; Project Catalyst; AVOID research programme, led by the Met Office Hadley Centre; UNEP Risoe; and the World Resources Institute; Climate Action Tracker, Climate Analytics for the research projects and C-ROADS; WITCH; GAINS; ENV-linkages; FAIR for the models). A total of 223 emission pathways produced by 15 modelling groups have been analysed. Pathways for different temperature targets (<2, 2-2.5, 2.5-3, 3-3.5, 3.5-4, 4-5, >5) with a likely (>66%) chance being below the targets of temperature increases have been produced. The pathways include several near term targets too. The subsequent UNEP Emissions Gap Report 2013 [5] includes reviews of the results from projects that are listed in this report (LIMITS, EMF and AMPERE) as well as some single model studies. 9 Table 1: List of models involved in the projects included in the report. Model name Model category Solution Algorithm AIM / AIMEnduse Partial equilibrium Recursive dynamic BET General equilibrium Intertemporal optimization China Partial MARKAL equilibrium Dynamic linear optimisation DNE21+ Partial equilibrium Intertemporal optimization GCAM / Partial equilibrium Recursive dynamic General equilibrium Intertemporal optimization GCAMIIM EC-IAM Reported Land use sector representation Coverage of greenhouse gases 2050 Marginal Abatement Costs (MACs) for land use emissions All GHGs and other radiative agents 2100 None (land use emissions exogenous) CO2 2050 MAC curves for souces CO2 2050 MACs for land use emissions All GHGs and other radiative agents 2100 Endogenous land use dynamics, Afforestation option All GHGs and other radiative agents None Kyoto gases from fossil fuel combustion and industry 2050 MACs for land use emissions Kyoto gases 2100 Land is competed across crops, pasture, forests, and biomass CO2 from fossil fuel combustion and industry time horizon 2100 ENVgeneral Linkages equilibrium Recursive dynamic FARM general equilibrium Recursive dynamic GCAM Partial Equilibrium Recursive dynamic 2100 Endogenous land use dynamics full basket of greenhouse gases, precursors and aerosols GEM-E3 general equilibrium Recursive dynamic 2100 best allocation between food/ energy crops production All GHGs GRAPE General equilibrium Intertemporal optimization Endogenous land use dynamics All GHGs and other radiative agents IMACLI M general equilibrium Recursive dynamic None CO2 from fossil fuel combustion and industry IMAGE / TIMER Partial equilibrium Recursive dynamic 2100 Endogenous land use dynamics All GHGs and other radiative agents IPAC Multi-model framework links several models 2100 Land equilibrium model All GHGs 10 2100 2100 MERGE General equilibrium Intertemporal optimization MACs for land use emissions, All GHGs and other radiative agents 2100 No CO2 emissions from land use MESSA GEMACRO General equilibrium Phoenix general equilibrium Recursive dynamic Partial equilibrium Recursive dynamic General equilibrium Intertemporal optimization POLES REMIND Intertemporal optimization 2100 MACs for land use emissions All GHGs and other radiative agents Afforestation option TIAMECN Partial Equilibrium Intertemporal optimization TIAMWorld Partial equilibrium Intertemporal optimization WITCH General equilibrium Intertemporal optimization WorldSc an general equilibrium Recursive dynamic None CO2 from fossil fuel combustion and industry None Kyoto gases from fossil fuel combustion and industry All GHGs and other radiative agents 2100 Baseline land use emissions from land use model MAgPIE coupled to MACs, endogenous land use dynamics from MAgPIE in some scenarios 2100 None - exogenous CO2, CH4, N2O. 2100 MACs for land use emissions Kyoto gases with the exception of FGases MACs for land use emissions Kyoto gases 2050 2100 2100 2100 3. Pathways description Within Table 2 (physical climate parameters) we have listed the scenarios that are broadly consistent with a 2°C (in green) and a 2.5°C (in amber) target. It should be noted that all these scenarios represent ambitious goals with dramatic changes in anthropogenic GHG emissions. Limitations to comparing scenarios Comparing the findings of different scenarios can be difficult, although not impossible, in part due to the variety of ways the targets within different studies are set. Targets used by studies include: 11 1. the maximum temperature in 2100 [4]; 2. the Representative Concentration Pathway (RCP) describing the radiative forcing [24] and [25]; 3. the maximum concentration of GHGs (LIMITS, AMPERE, RoSE, EMF27); 4. the emissions pathways (EMF27 with Fragmented Policy and G8 commitment policy [7]). Another possible limitation in comparing the scenarios of different studies, noticeable in Table 3 (Socio-economic parameters), is the diverse socio-economic storylines that supports scenario developments for modelling. Within the LIMITS project alone, 2050 GDP varies between USD 103 to USD203 trillion depending on the model used. In the same way population in 2100 is assumed to range from 8.7 to 10 billion with possible stabilisation at the end of the century. The second group of scenarios shows consistency toward a temperature change in 2100 below the 2.5°C target and are all converging toward the 550ppm CO2 concentration in 2100. This group also allows a delayed peak year - until 2035 - with higher peaking emission quantities in certain cases. Pathways broadly consistent with meeting 2°C or below Based on 2°C target studies, it seems that 500 ppm is the maximum permissible CO2-eq concentration in 2100, with emissions peaking in 2030 at the latest; the later peaking dates proving less cost-effective and relying heavily on CO2 removal technologies such as CCS. Most of these scenarios will also have to exhibit negative CO2 emissions at the end of the century. A few of these scenarios indicate an expected temperature change below 2°C in 2100 (between 1.5 and 1.8°C): RCP2.6, EMF27-450 and UNEP_Gap_Report_1.5°C. Generally the mean annual GHG emissions reduction rate, following the peak, is between 2 to 5% when the peak year is around 2020. Later peaking pathways will lead to larger rates of GHG emission reduction (from 6 to 8% per year) and require negative emissions at the end of the period to comply with the target with a temporary overshoot. Although the rapid reduction in global emissions in some scenarios is technically and economically feasible within the modelling framework, political decisions, social acceptance and institutional factors will also play a major role in the real world – elements which are not part of the modelling framework, other than through the mechanism of delayed or regionally fragmented action. Focussing at national level, some examples of very rapid emissions reductions can be found in the recent past: during the 1980s France was reducing emissions at a rate of 4 to 5% per year as a result of the large-scale deployment of new nuclear power plant facilities; the UK sustained a reduction reaching 2% per year in the 1970s decade by a strong switch from coal to gas in electricity production. These examples highlight the practical rates achievable through technical changes; however the recorded reductions lasted only a decade or less, and were at country levels as opposed to the global level required in the scenarios discussed in this paper. In the literature maximum possible global reduction rate can be extracted; for example maximum annual rates of 3.5% [2] and 4.3% [26] take into account assumptions about technological development, economic costs, and/or socio-political factors. In some scenarios analysed for this study the emission reduction rates can reach 8 to 10% per year are largely exceeding these possible maximum values. 12 In all of these scenarios the only geoengineering technology explored to mitigate climate change is bio-energy coupled with CCS (BECCS) that could produce negative emissions during the end of the century. Particularly in scenarios with later peaking years, BECCS is therefore a critical technology, and its absence often results in an inability for models to meet the prescribed target where this is relatively stringent (i.e. consistent with 2 °C or less). Pathways broadly consistent with remaining under 2.5°C by 2100 Pathways in agreement with relaxed target achieving between 2°C and 2.5°C show different behaviours in term of physical climate factors. Those pathways are coloured in amber in the Table 2. The concentrations of GHG in 2100 can reach the range 500 to 550 ppm. Mostly in this case the peak of emissions is allowed to be delayed till 2035 with, after this peak, emission reduction rates between 3 to 4%/y closer to the accepted maximum range discussed above. Finally and crucially in these pathways overshoot in radiative forcing is occurring rarely and the all scenarios still show a positive GHG emission in 2100 in the range of 1 to 20 GtCO2. 13 Table 2: Physical climatic parameters Study / model / scenario GHG concentration / ppm of CO2eq in 2100 Temperature GHG pathway peak change by 2100 year and CO2 level EMF27 450 450ppm 1.5-1.8°C (target on RF=2.6 Wm-2) 2025=20to35 GtCO2eq LIMITS FP7 450ppm 450ppm 1.7±0.1°C EMF27 G8 480 to 500ppm LIMITS FP7 500ppm 500ppm AMPERE 450 immediate action 14 450ppm CO2 reached by 2050, by 2100 Forcing Wm-2 by 2100 2050=8to15 / 2100=20to0 GtCO2 2.5 to 2.9 Cumulative 2010(overshoot 2100=1750–2300 GtCO2-eq 3 to 3.5 around 2050) 2020-30=2.8,203040=5.3,204050=5.2%/y mean ensemble 2020=53±1 GtCO2eq 2050=25±2 / 2100=0±1 GtCO2 2.8 2011-2050= (overshoot 860to1270, 20113.0) 2100= 1720to2090 GtCO2-eq 2020-30=2.8,203040=5.3,204050=5.2%/y mean ensemble 1.8-2.3°C 2020to2030=25to35 GtCO2eq 2050=10to20 / 2100=0to20 GtCO2 3 to 3.8 NA 1.9±0.15°C 2020=53±1 GtCO2eqGtCO2 2050=35±2 / 2100=1±1 GtCO2 3.2 2011-2050= 1500to1940, 20112100= 2100to2720 GtCO2eq 2020-30=2.7,203040=3.8,204050=4.2%/y mean ensemble 1.9°C (1.7–2.5) probablity >2°C=36% 2020=45±5 GtCO2eq 2050=25±2 / 2100=2±2 GtCO2eq 2.8 (max 3.3) 2011-2050= 1689 GtCO2-eq (1084– 2261), 2011-2100= 2289 (1273–2708) 2030-50=4%/y mean ensemble (3 to 4.5) O C above preindustrial Cumulative CO2eq budget 2011-2050, 2011-2100 Rate of emissions reduction from peak year to 2050 RCP 2.6 455ppm (2050) 1.9°C (0.9-2.3°C 427ppm (2100) min to max range CMIP5) 2020, 37.6 GtCO2 12.4 (2050), -1.5 (2100) GtCO2 2.7 2011-2050= 5501,270, 2011-2100= 630-1,180 GtCO2 N/a RoSE Immediate action 450ppm 2°C with 50% chance 2010, at 45 GtCO2eq, although one model (GCAM) peaks in 2035, at 50Gt CO2eq 25-30 GtCO2eq by 2050 / 2.6 (peak 3.4) Not specified Not specified RoSE delayed action to 2020 450ppm 2°C with 50% chance 2020 peak at 50-57 GtCO2eq 20-25GtCO2eq in 2050 / 2.6 (peak 3.5) Not specified Not specified RoSE delayed action to 2030 450ppm 2.6 (peak 3.8) Not specified 10%/y between 30302040 (maximum rate) 3.4 (max 3.8) 2011-2050= 2155 GtCO2-eq (1500– 2289), 2011-2100= 2756 (1732–3071) 2030-50=7.5%/y mean ensemble (6.5 to 8.5) NA 2030-2050=2to4.5%/y (late action=6to8.5%/y) 5 GtCO2eq in 2100 15 2030 peak at 5565GtCO2eq 17-22GtCO2eq in 2050 / 0-5 GtCO2eq in 2100 AMPERE 450ppm 450 delayed action UNEP Emissions Gap Report 2013 2°C with 50% chance highest 450ppm for CO2 2.1°C (2.0–2.5) probability >2°C=60% 2020to2030=45±5 GtCO2eq 2050=20±3 / 2100=0±2 GtCO2eq Target 2°C with likely chance >66% 2010-2020 36to47 GtCO2eq (2020 median=40,42,44) 2050=20,21,22GtCO NA 2eq / 2100:1/3models negative emissions UNEP Emissions Gap Report 2013 highest 450ppm for CO2 UNEP Emissions Gap Report 2013 highest Target 1.5°C 450ppm for CO with medium chance (50to66%) Target 2° C with medium chance (50to66%) 2010-2020 44to49 GtCO2eq (2020 median=46) 2050=25to32GtCO2e NA q (28med) / 2100:1/3models negative emissions NA NA 2010-2020 37to44 GtCO2eq 2050=5to18GtCO2eq NA (28med) / 2100:few scenarios negative emissions NA 2030-2050=2to4.5%/y (late action=6to8.5%/y) 30-70% reduction in 2050 compared to 2005. Negative in 2100. NA NA NA Global NA Energy Assessment 2°C with at least 50% chance 2020 Peak year. CCC2013UCL 440ppm for CO2, in line with 2°C in 2100 2° C 2016 peak 36 GtCO2. 13.9 GtCO2 in 2050 / 35.0 GtCO2 in 2020 5.0 GtCO2 in 2100 (Early action) 2.99 (peak 2010-2050= 1462 / 3.17 in 2010-2100= 2400 2050) GtCO2-eq 4.00% CCC2013UCL 450ppm for CO2, in line with 2°C in 2100 2.1° C 2025 peak 41GtCO2. 39.9 GtCO2 in 2020 (Later action) 13.9GtCO2 in 2050 / 5.0 GtCO2 in 2100 3.2 (peak 3.47 in 2050) 4.50% CCC2013UCL 465ppm for CO2, in line with 2°C in 2100 2.15° C 2025 peak 41GtCO2. 39.9 GtCO2 in 2020 (Reduced action) 20.9GtCO2 in 2050 / 5.6 GtCO2 in 2100 3.44 (peak 2010-2050= 1775 / 3.61 in 2010-2100= 2880 2070) GtCO2-eqGtCO2-e 16 2010-2050= 1710 / 2010-2100= 2650 GtCO2-eqGtCO2-e 2.00% RCP 4.5 500ppm (2050) 1.7-3.2°C (min to 2035= 42 GtCO2 540ppm (2100) max range CMIP5) 40 GtCO2 (2050) 12 GtCO2 (2100) 4.5 2011-2050= 1,2601,640, 2011-2100= 1,870-2,430 GtCO2 NA EMF27 550 550ppm 2-2.3°C (target RF=3.7 Wm-2) 2025to2030=25to40 GtCO2eq 2050=10to20 / 2100=0to20 GtCO2 3.4 to 3.8 Cumulative 20102100=2460– 3260GtCO2-eq 2020-30=2.7,203040=3.8,204050=4.2%/y mean ensemble AMPERE 550 immediate action 550ppm 2.3°C (2.1 to 2.8) probability >2°C=73% 2030=60 GtCO2eq 2050=20±2 / 2100=1±2 GtCO2eq 3.7 (max 4.0) 2011-2050= 2019 GtCO2-eq (1460– 2420), 2011-2100= 3251(2330–3643) NA AMPERE 550ppm 550 delayed action 2.4°C (2.2–2.6) probability >2°C=76% 2030=60 GtCO2eq only EU road map 2050=20±2 / 2100=1±2 GtCO2eq 2011-2050= 2198 GtCO2-eq (1695– 2384), 2011-2100= 3287 (2584–3619) NA RoSE 550 2.4 °C (2.2–2.6) 2020 (50 GtCO2eq) – 30-40 GtCO2eq 2030 (50-55 (2050) GtCO2eq) Not specified 2030-2050 = 3%/yr (maximum rate across the models) 17 550ppm 3.9-4.2 4. Socio-economic assessment Globally, economic and population growth continue to be some of the most important drivers in increasing CO2 emissions. Whilst between 2000 and 2010 the contribution of population growth to GHG emissions has remained roughly identical to the previous three decades, during this same period of time the contribution of economic growth has risen sharply [22]. Further, without additional efforts to reduce GHG emissions beyond those in place today, emissions growth is expected to persist driven by growth in global population and economic activities. The studies examined assumed a range of increases in global population sizes and economic growth, with a high variation noted in the range of economic growth estimates between studies. This is, in part, due to there being more uncertainties in estimating economic growth than population increase. Estimated population growth In most studies, 2050 population is estimated at around 9 billion while 2100 population assumptions vary from 9.1 billion (LIMITS and RCP 2.6) to 10 billion (AMPERE). Within the EMF 27 project variation in population growth exists between models as no socioeconomic harmonisation was required. One of the RCP scenarios (RCP 4.5) assumes global population peaking in 2065 (9 billion) and then sees a fall to 8.7 billion in 2100 in contrast with estimates in other scenarios, in which population continues to rise until the end of the century. Most of these studies did not explicitly discuss future urbanisation rates, which is one of the key drivers that contribute to increasing per capita emissions, especially in the emerging economies in the near and medium term and in developing countries in the longterm. As of 2011, more than 52% of the global population lives in urban areas whilst in 2006, urban areas accounted for 67–76% of energy use and 71–76% of energy‐related CO2 emissions; by 2050, the urban population is expected to increase to 5.6–7.1 billion, or 64– 69% of world population [22]. Estimated economic growth Global studies such as UNEP Emissions Gap Report (UNEP, 2013) and Global Energy Assessment 2012 assume per capita GDP growth of 2% per year to 2050, mostly driven by developing countries, while the UCL-CCC 2013 [20] and AMPERE studies assume slightly higher growth rates of 2.4% and 2.7% respectively. EMF 27 assumes an average growth rate of 1% per year to 2100. 18 Table 3: Socio-economic parameters Study / model / scenario Economic growth rate to 2050, to Population growth 2100 AMPERE global average growth=2.7% per year 2100=10billions / medium fertility variant of the 2010 version of the UN World Population Prospects CCC2013-UCL 2.4% to 2050 9.3 billion 2050 EMF27 annual average 1% in 2100 9 billions 2050 to 9.6 2100 (stabilisation) Global Energy Assessment 2%/year to 2050 about 9 billion in 2050 (Urban population 6.4 billion in 2050) LIMITS FP7 GDP 2010=54 (mean) 2050=103to203 (model dependant) 2100=730(TIAM-ECN only) 9.2, 9.1 billion (TIAM_ECN only) RCP 2.6 2000=$34, 2030=$84, 2100=$229 trillion (1995 $US) 8.2 billion (2030),9.1 billion (2100) RCP 4.5 2000=$40, 2030=$75, 2095=$330 trillion (2005 $US) (2005) 8 billion (2030), 9 billion (2065=peak),8.7 billion (2100) UNEP Emissions Gap Report 2013 per capita GDP growth rate is 2% to NA 2050 5. Technology parameters This section highlights the technologies included in the different scenarios. The usual approach in the majority of the projects included in this report is to use a business-as-usual or reference scenario to compare to a series of mitigation scenarios (of different levels of stringency) involving a large portfolio of technologies available at specified costs. These “full technology portfolio” scenarios usually allow strong and rapid developments in renewable or other low-carbon technologies in the power sector as well as the deployment of new technologies such as CCS. Energy efficiency improvement options in final energy demand sectors are also included, but treated as separate from the group of energy generating technologies. In these “full portfolio” modelling exercises technology costchanges over time can occur through two channels: learning-by-doing (experience gained during development) or learning-by-searching (research and development activities). These improvements can induce new dynamics between technology adoptions and create divergences among model results (LIMITS and EMF27). However in most model scenarios, technology costs are specified as a set of input assumptions. Technological challenges are studied in a series of further scenarios including limitations on the availability of specific technologies or groups of technologies. The usual technology 19 restrictions (which are assumed to follow from technical limits or political decisions to restrict technology deployment) in these alternative scenarios are: a nuclear phase out, no CCS development, reduced deployment of wind and solar because of intermittency limits, and finally reduced availability of biomass as an energy feedstock. Some scenarios are calculated with a combination of these restrictions. In the baseline scenarios the energy demand increase is met primarily with carbon intensive fossil fuels; generally the CO2 emissions for 2050 reach 2 to 3 times the 2010 levels. Within the full technology portfolio scenarios decarbonising the electricity generation sector is one of the main approaches to achieving the targets. The share of low-carbon generation in the electricity supply increases from 30% today to 80-100% decarbonisation in 2050 (depending on the stringency of the climate target). Within the total primary energy sources, low-carbon sources represent only between 60% and 70% in these scenarios highlighting the more difficult decarbonisation of other sectors (such as transport) compared to electricity generation. Renewable technologies such as wind and solar commonly take the largest share of low-carbon electricity generation in 2050. The share of CCS in electricity generation in 2050 varies from 8% to 32%. This is partly driven by assumption on CCS deployment, which starts in or after 2025 in all scenarios, and assumptions deployment renewable technologies. However this fact changes during the second half of the century when CCS technology becomes more mature and renewable generation reaches saturation; this is particularly the case in scenarios with stringent targets or overshoots when BECCS in the second part of the century is needed to create negative emissions. 20 Table 4: Technology parameters Study / model / scenario Key technology transitions Technologies Deployment constraints excluded AMPERE 450ppm immediate action Decarbonisation power generation, substitution of fossil fuel with electricity in stationary, transport electrification, acceleration of energy efficiency improvements: renewable+storage+gas-fired capacity. Nuclear, CCS AMPERE 450ppm delayed action Nuclear and CCS critical only if delayed action 2030 None CCC 2013/ TIAM-UCL Decarbonisation occurs foremost in the power sector and, with the CO2 intensity decreasing from over 500 g/kWh in 2010 to 54 g/kWh in 2030 and to 1.5 g/kWh in 2050. EMF 27 Near-term: decarbonisation of electricity Long-term: increase in use of electricity in end-use and appropriate mix of technologies for decarbonizing electricity depends on assumptions about supply technology characteristics and availability. 21 Sensitivity analysis has been carried out without CCS technology Constraints added to solar, wind and biomass: E.g. biomass 100 EJ/year, maximum 20% electricity from solar and wind together. As above Build rate constraints: 15%/year for CCS (coal, gas and biomass); 15%/year for PV and 10%/year for wind. New nuclear capacity addition per year is constrained to 30 GW in 2030 and 60 GW in 2050. Biomass potential (energy crops and solid biomass) is limited to 10,600 TWh/year. No CCS and Solar & wind 20% max share. Biomass is nuclear phase constrained to 100EJ/y out GEA 2012 (analysed 60 alternative transitions) / MESSAGE and IMAGE Cumulative CO2 capture up to 250 Gt in 2050. None Not reported None Not reported None Not reported Complete phase-out of coal power without CCS by 2050. Strong bioenergy growth from 45 EJ in 2005 to 80– 140 EJ by 2050 (co-firing with coal or gas with CCS). Low carbon electricity ranges from 75%-100% in 2050 LIMITS FP7 450 ppm Electricity generation annual new capacity: 2010-30: wind 60, Solar 30, Nuclear 30, and CCSFF 15 GW (6 models average) 2030-50: wind 145 / solar 175 / Nuc 45 / CCSFF 80 / BECCS 25 GW (6 models average) RCP 2.6 11 GtCO2 stored annually 350 EJ of bioenergy [Van Vuuren 2007] RCP 4.5 Electricity sector becomes carbon negative by 2100 (40% nuclear, 20% coal w/CCS, 10% gas w/CCS, 5% hydro, 5% biomass w/CCS, 20% other) None Not reported RCP 6.0 By 2100 CCS deployed on 74% of thermal fossil power plants, share of non-fossil power plants exceeds 30% None Not reported 22 RCP 8.5 Fossil fuels dominate (coal use multiplies tenfold throughout century) and renewables learning rates are low (10% price reduction for each doubling of capacity). None Not reported RoSE All three models (WITCH, REMIND, GCAM) show significant reduction in final energy demand by 2100, between 20% (REMIND) and 55% (WITCH) lower than in the baseline. None In GCAM, biomass availability is limited to 210 EJ/year. In REMIND, existing capital can be prematurely retired, but only up to 4%/year of installed capacity. None Not reported UNEP-Emissions Gap Net negative emissions in 2100. Report 2013 Bio-energy with CCS in the second half of the centaury 23 6. Mitigation policies There are three ways for pricing carbon to reduce CO2 emissions [28]. 1. Carbon taxation (tax); 2. Carbon trading on the basis of trade in rights to emit which are allocated or auctioned (cap-and-trade); 3. Implicit pricing via regulations and standards, which impose constraints on technologies that can be necessary where irremovable or unavoidable market imperfections exist. The interactions between these mitigation policies may be synergistic, or may have no additive effect on reducing emissions [22]. For instance, a carbon tax can have an additive environmental effect to policies such as subsidies for the supply of renewable energy. By contrast, if a cap and trade system has a binding cap (sufficiently stringent to affect emission‐related decisions), then other policies such as renewable energy subsidies have no further impact on reducing emissions within the time period that the cap applies. In either case, additional policies may be needed to address market failures relating to innovation and technology diffusion. Modelling studies either use (in the case of bottom-up least-cost optimisation models) a cap and generated “shadow” prices for carbon (i.e. carbon prices which if imposed would generate the same least-cost solution as that reported) or (in the case of top-down macroeconomic models) apply a carbon price in order to analyse impacts on emissions, as a result of changing the relative prices of carbon-intensive energy and alternative energy. Additional policies or constraints implemented in the modelling exercises, which are important in determining the feasibility of meeting global climate change mitigation targets, are near-term mitigation pathways (including caps or targets for specific near-term dates, often to simulate levels of effort commensurate with the Cancun pledges), the choice of emissions peaking year, and the method by which effort is shared between regions (e.g. through equal per capita emissions, equal marginal abatement cost, or some other burden-sharing principle), as well as whether regions can freely trade carbon permits with each-other. Global studies almost invariably suggest that early action is preferred (Table 5: Policy parameters), as it will reduce overall mitigation cost and mitigation uncertainty. It will also avoid the risk of locked in investment in high carbon technologies, which will increase overall mitigation costs through early capital scrapping. Though most of the studies suggest early action is preferred, the peaking year and peaking emissions level vary across the studies. For example, the Global Energy Assessment (IIASA, 2012) reports that limiting global temperature increase to less than 2°C over pre-industrial levels (with a probability of >50%) is achieved in the pathways through rapid reductions of global CO2 emissions from the energy sector, peaking around 2020 and declining thereafter to 30–70% below 2000 emissions levels by 2050, ultimately reaching almost zero or even net negative CO2 emissions in the second half of the century. Higher CO2 prices in 2050 are generated the longer the delay in implementing global emissions reductions (i.e. the later the date at which global emissions peak) and the greater the required level of emissions reductions [20]. 24 Table 5: Policy parameters in mitigation scenarios Study / model / scenario Effort sharing / carbon trading assumed? Delayed action? AMPERE extrapolation current policies Fragmented policy Peak: 2060-270 AMPERE 450ppm immediate action Strong global action No CCC 2013-UCL: Core Equal per capita emissions of 1.5tCO2/person in 2050 Peaking in 2016 CCC 2013-UCL: Later Equal per capita emissions of action 1.5tCO2/person in 2050 Peaking in 2025 CCC 2013-UCL: Reduced action Equal per capita emissions of 2tCO2/person in 2050 Peaking in 2025 EMF 27 None Harmonised policy=least cost mitigation options, globally uniform carbon price / Fragmented policy: Group I (no Russia) -50% emission in 2050; Group II slower reduction + limited emission trading with Group I; Group III: no policy (fossil fuel producers + Russia) LIMITS FP7 450 ppm Burden sharing after 2020 (2 policies: per capita convergence and equal effort) Peak 2020 RCP 2.6 N/a Emissions reduction begins in 2020 RCP 4.5 Yes - assumes a common global price is shared across regions. No – carbon price rises at a fixed rate annually until the forcing level is reached, then remains roughly constant. RCP 6.0 Yes – assumes a global emissions permit market Yes – no carbon price until 2050. However relative to baseline carbon intensity per unit energy dos decrease in period to 2050. RCP 8.5 N/a N/a RoSE Carbon trading established following any delays in action RoSE explores immediate action, delayed action until 2020, and delayed action until 2030. 25 7. Technology and cost implications The pathways indicate that the energy transformations need to be initiated without delay, gain momentum rapidly, and be sustained for decades. This requires the rapid introduction of policies and fundamental governance changes toward integrating climate change into local and national policy priorities. A range of measures is required in each sector. For example, as discussed in the GEA [17], rather than aiming for buildings that use zero fossil fuel energy as quickly as possible, an economically sustainable energy strategy would implement a combination of the following: reduced demand for energy; use of available waste heat from industrial, commercial, or decentralized electricity production; on-site generation of heat and electricity; and off-site supply of electricity. Some assessments, notably the IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation [27] and the GEA [17] emphasize the great importance of accelerating demand-side efficiency and conservation measures for future reductions of greenhouse gas emissions. Fossil fuel consumption in higher-income regions consequently falls (as shown in Table 6: technology and cost implications), and there is resultant downwards pressure on fossil fuel prices. Cheaper resources are therefore available to the middle and low-income countries and so there is almost no additional cost to these regions in 2020 (while marginal, the change in cost is still positive, however.) The assumption of perfect foresight means that some of the middle and low-income regions do implement some emissions reduction (albeit at a much lower level of ambition than in high-income regions) [21]. Long infrastructure lifetimes mean that it takes decades to change energy systems; so immediate action is needed to avoid lock-in of invested capital into existing energy systems and associated infrastructure that is not compatible with longer climate targets [17]. Infrastructure developments and long‐lived capital stocks that lock societies into GHG‐intensive emissions pathways may be difficult or very costly to change, reinforcing the importance of early action for ambitious mitigation. This lock‐in risk is compounded by the lifetime of the infrastructure, by the difference in emissions associated with alternatives, and the magnitude of the investment cost. As a result, lock‐in related to infrastructure and spatial planning is the most difficult to reduce [22]. The largest threat of lock-in of technologies within the energy system regards electricity production from fossil fuel (for coal and gas) and has been considered in the case of a 2°C target following scenarios with different short term emission reduction goals within the AMPERE and the RoSE projects. Currently, about 90% of global primary energy supply comes from coal, oil and gas. Climate policy and pricing of CO2 emissions are likely to make some of the fossil installations unprofitable, thus resulting in pre-mature retirement of fossil capacities before the end of their technical lifetimes. In the AMPERE project, a range of GHG emissions targets are specified (from 50 to 60GtCO2eq), with the long term target in all cases fixed below 2°C. Scenarios with higher short term targets have to rely heavily on negative emissions at the end of the century to achieve the long term goal. More importantly, with these less stringent short term targets the phase-out of coal (and gas) capacity in electricity production is delayed until after 2030 and as a consequence fossil fuel generation capacity continues to be built in the period to 2030; in this case the phase-out of coal and gas production, to totally decarbonise the electricity system in 2050, creates stranded capacity in the electricity generation sector. In the worst case (the highest 2030 target) the stranded investment reaches globally $60billion for the 2010-2030 period and almost $450billion for 26 the 2030-2050 period with a particularly large contribution from China and South Asia, which will have invested heavily in coal generation during the first period. The 2030-2050 costs for these two regions represent more than 10% of their total investment in electricity generation during the period. To avoid these large stranded capacities fixing lower short term targets are effective (targets below 53GtCO2eq in 2030 reduce the above costs by two thirds). Other less effective options available to avoid high costs from stranded capacity are reducing energy demand (increasing efficiency), retrofitting old coal and gas capacity with CCS (if available) and increasing the lifetime of existing coal capacity (instead of building new ones). The RoSE results for similar scenarios show that in 2030, between 600 and 1400 GW of fossil power generation capacity are idle in the best policy case with immediate action. Early retirements peak later and at a higher level (up to 3,500 GW) in the delayed scenarios. There is some variation in total energy system costs at a regional level. In 2020, overall costs are higher in high-income regions since these are required to meet their Copenhagen Accord emissions reductions. This switches after 2020, with a greater proportional cost in middle and low-income regions [21]. For middle-income regions, the rapid increases in energy-service are predominantly met through an increase in coal consumption. Given that coal consumption needs to be severely restricted in 2°C scenarios until CCS is fully available, these regions require a greater level of investment to meet the emissions reductions required. In low-income regions it is assumed that the unit capital costs of many of the lowcarbon technologies (such as CCS) are higher than in the high-income regions. These are consequently more expensive to deploy and overall costs are higher. According to IIASA [17], in order to achieve the 2°C target, at least a 60–80% share of global primary energy will need to come from zero-carbon options by 2050; the electricity sector in particular will need to be almost completely decarbonized by mid-century (low carbon shares of 75–100%). Getting to that point requires a complete phase-out of coal power without CCS by 2050 with strong bioenergy growth in the medium term (co-firing with coal or gas with CCS). Natural gas acts as a bridging or transitional technology in the short to medium term and provides ‘virtual’ storage for intermittent renewables. In these scenarios nuclear energy is a choice, not a requirement. In IPCC 2014 [22] substantial reductions in emissions would require large changes in investment patterns. Mitigation scenarios in which policies stabilize atmospheric concentrations (without overshoot) in the range from 430 to 530 ppm CO2eq by 2100 lead to substantial shifts in annual investment flows during the period 2010–2029 compared to baseline scenarios. Over the next two decades (2010 to 2029), annual investment in conventional fossil fuel technologies associated with the electricity supply sector is projected to decline by about USD 30 (2–166) billion (median: ‐20% compared to 2010) while annual investment in low‐carbon electricity supply (i.e., renewables, nuclear and electricity generation with CCS) is projected to rise by about USD 147 (31–360) billion (median: +100% compared to 2010). Carbon prices are also assessed for the mitigation scenarios. The carbon price tends to rise over time when emissions mitigation effort increases and as a consequence becomes more expensive to achieve. The inter-model spread in carbon price increases as the required emissions reduction effort increases, because the models have different technical capabilities and costs for deep levels of mitigation. The targets analysed in this report corresponding to temperature goals lower than 2°C and 2.5°C are stringent and as 27 consequences the carbon price reported can diverge amongst models within the same project. The carbon prices for the 2°C target pathways, in the optimum case scenarios of early adoption of mitigation policy and availability of all key low-carbon technologies in the models, range between $15-$115 per ton of CO2 in 2020 and increase to $30-$140 in 2030, $80-$900 in 2050 and $110-$4000 in 2100 (prices in US$2010). The less stringent 2.5°C pathways display lower prices mostly before 2050, then after the mid-century the carbon prices reach similar levels as those for the more stringent target. These values are presented for the optimal case scenarios; any delays in policy adoption or failure in one of the lowcarbon technologies assumed will rapidly change and increase these prices. Few studies (for example AMPERE) reported macroeconomic costs of climate change mitigation policies. Generally macroeconomic costs increase with the stringency of the target and are higher for the pledge pathways. Delayed action, in general, increases the global mitigation costs and also leads to a possible fossil fuel lock-in of the electricity system, creating large and expensive unusable assets. As such the most cost-effective scenarios to achieve the 2°C target are characterised by early mitigation creating clear signals for lowcarbon technology investments and a near term peak in emissions (with the latest possible peaking dates occurring between 2025 and 2030, and with peak GHG emissions in the range of 30 to 50 GtCO2-eq). In the optimal policy scenarios (AMPERE), consumption losses (2010-2100) are between 0.6-6.5%. The comparable range of the early action scenarios is between 0.6-6.8 %, and for the late action scenarios between 0.7-6.8 %. Consumption losses for the least cost pathways to reach the 2°C target in 2100, with the assumption that all mitigation technologies are available (including all major renewables, nuclear and CCS), are in the range of 2 to 6% in 2050 and 3 to 11% in 2100 relative to the no mitigation (or “business as usual”/baseline) scenarios. 28 Table 6: Technology and cost implications Study / model Share of / scenario fossil fuels in primary energy by 2050, 2100 GW deployed of key technologies (solar, wind, CCS, nuclear) Change in Shadow carbon Consumption energy intensity price in 2020, 2030, losses in 2020, of GDP, 20112050, 2100 2030, 2050, 2100 2050 For each sector: % reduction in primary energy relative to baseline by 2050/2100 N/A AMPERE extrapolation current policies N/A N/A 2030: up to 30$/tCO2 N/A N/A AMPERE 450 immediate action N/A Renewable share of primary N/A energy 2050=30%, 2100=55% 2050=150 $/tCO2 0.6 to 4 % loss (cumulative 20102100 with 5% discount rate) N/A AMPERE 450 delayed action N/A Renewable share of primary N/A 2050=18% (≈2010) / 2100=65% 2050= 450 to 750 0.5 to 3.7 % $/tCO2 (high or low 2030 targets) N/A AMPERE 550 immediate action N/A N/A N/A 2050=80 $/tCO2 0.25 to 2% (in 1 model -1.2%) N/A AMPERE 550 delayed action N/A N/A N/A 2050= 90 to 100 $/tCO2 (high or low 2030 targets) 0.2 to 1.9% N/A 29 CCC 2013UC: core N/A N/A EMF 27 BAU N/A EMF 27 550 EMF 27 450 Core: in 2005$/tCO2, 219 in 2030, 889 in 2050 N/A N/A S=3 (1to12), W=15 (5to20), N/A N=39 (0to66) EJ/y Renewable electricity: 15% (10 to 20) / 18% (10 to 25) & Non-Electricity RE=2% (1 to 3) / 4% (1 to 6) & Nuclear electricity =9% N/A N/A N/A N/A 10 to 30% rel. to S=15 (5to25), W=25 (15to35), N=45 (8to68) EJ/y BAU Renewable electricity: =25% (22 to 32) / 40% (32 to 45) & Non-Electricity RE =4% (1 to 5) / 12% (5 to 16) & Nuclear electricity = 17% time-average carbon price 5 to 50 $/tCO2 0.3 to2.2 % loss (cumulative 20102100 with 5% discount rate) + one model 8% N/A N/A S=30 (10to35), W=33 (20to35), N=67 (11to214) EJ/y time-average carbon price 12 to 92 $/tCO2 0.8 to3.2 % loss (cumulative 20102100 with 5% discount rate) + one model 11.7% N/A Renewable electricity: =32% (28 to 36) / 55% (40 to 60) & Non-Electricity RE =6% (4 to 8) / 22% (10 to 26) & Nuclear electricity = 18% 30 N/A 15 to 50% rel. to BAU 1.5-2.2% annually to 2050 GEA 2012 N/A Nuclear 75-1850 GW in 2050. Renewable (164-651 EJ) 30-75% of primary energy in 2050. LIMITS FP7 450 ppm N/A 2010-30(25,60,15,25);2030- N/A 50(170,140,105,45)GW/y RCP 2.6 30% (2050) 10% (2100) RCP 4.5 40% (2050) N/A N/A CO2 price range in 2020 is 15110$tCO2 (200 prices) and it increases at a rate of 5% per year. N/A N/A N/A Cumulative 20102050: $45trillion comp to base N/A $60 tCO2 (2020) 0.3% (2020) $80 tCO2 (2030) 0.9% (2030) $160 (2050) 1.7% (2050) Primary energy reduced 20% compared to baseline in 2100 $200-250 (2100) 0.8% (2100) $85 tCO2 (2100) Primary energy down about 10% in 2100 cf baseline 60% (2100) RCP 8.5 31 80% (2100) N/A -0.5% per year N/A N/A N/A RoSE 450 immediate action 54-61% (2050) Up to 240 EJ/year of nuclear in 2100 18-23% (2100) Up to 106 EJ/year of fossil with CCS in 2100 2.0-2.6% per year to 2050 35-46 $/tCO2 (2020) 1.4-2.5% GDP loss cumulatively $62-105 (2030) over the period to $170-403 (2050) 2100 32-52% below BAU (2100) $1,200-4,900 (2100) Up to 300 EJ/year biomass (of which 195 EJ/year with CCS) in 2100 23-45% below BAU (2050) Up to 285 EJ/year of solar in 2100 RoSE 450 delayed action to 2020 50-61% (2050) Up to 240 EJ/year of nuclear in 2100 15-22% (2100) Up to 97 EJ/year of fossil with CCS in 2100 Up to 290 EJ/year biomass (of which 195 EJ/year with CCS) in 2100 Up to 275 EJ/year of solar in 2100 32 2.0-2.7% per year to 2050 0-26 $/tCO2 (2020) $67-116 (2030) $177-472 (2050) $1,500-5,600 (2100) 1.5-2.5% GDP loss cumulatively over the period to 2100 23-47% below BAU (2050) 36-53% below BAU (2100) RoSE 450 delayed action to 2030 42-58% (2050) Up to 130 EJ/year of wind in 2.0-2.9% per 2100 year to 2050 10-20% (2100) Up to 257 EJ/year of nuclear in 2100 Up to 280 EJ/year of biomass in 2100 (of which up to 196 EJ/year with CCS) 0-26 $/tCO2 (2020) $8-203 (2030) $212-630 (2050) 1.7-2.9% GDP loss cumulatively over the period to 2100 $2,300-7,500 (2100) 25-50% below BAU (2050) 34-54% below BAU (2100) Up to 309 EJ/year of solar in 2100 RoSE 550 59-77% (2050) Up to 118 EJ/year nuclear in 1.9-2.2% per year to 2050 2100 37-58% (2100) Up to 260 EJ/year biomass in 2100 (of which up to 192 EJ/year with CCS) Up to 213 EJ/year of solar in 2100 Up to 255 EJ/year of fossil with CCS in 2100 33 13-30 $/tCO2 (2020) 1.5% GDP loss cumulatively over $25-49 (2030) the period to 2100 $88-137 (2050) $170-1495 (2100) 18-31% below BAU (2050) 15-45% below BAU (2100) 8. Co-benefits and secondary impacts of mitigation options Co-benefits and risks are intrinsic to mitigation options chosen for the global transformation pathways implemented. The large reduction in GHG emissions necessary to fulfil the stringent targets presented in the report has a significant effect on the energy system (from primary energy mix to final demand levels). These changes to the energy system induce side-effects including possible health benefits, changes to energy security or impacts on biodiversity. These effects are challenging to weight against the costs of mitigation as they apply to different systems (economic, social and environmental) and are measured in different units. Some integrated assessment models such as PAGE [29] or FUND [30] amalgamate some of these side-effects in a relatively simple manner to the global economic impact of the pathways but debates arise from the materialisation of such side-effects into monetary quantities. Within a small number of the studies included in the report two cobenefits to mitigation scenarios are reported: impacts on air pollution and energy security. Impacts on global air quality The impact on air pollution is reported in AMPERE and the RCPs scenarios as avoided emissions of NOx and SO2, two important precursors to air quality pollutants: ozone and particulate matters. These two pollutants have negative impacts on human health, crop production and building preservation. The reduction in emitted quantities is reported due exclusively to climate considerations – no air quality policies are included. For mitigation scenarios achieving a concentration of 450ppm CO2e, the models show strong reductions in NOx (for example 60% below the baseline in 2050 for RCP 2.6) and more modest reductions for SO2 (for example 20% below the baseline for RCP2.6). However, no direct effects on health and morbidity or on crop production are directly reported within the studies. Impacts on energy security Within the EMF27 project energy security is analysed for the mitigation scenarios compared to the baseline energy system. The reported information is orientated toward the qualitative analysis of energy system security. The study shows that mitigation policies in general increase national energy sufficiency and resilience via an increase and diversification of energy sources and carriers. In LIMITS the policy scenarios are combined with large reductions in fossil fuel dependence (and as a consequence imports) that increases energy security after 2030. The RoSE project reports that 450ppm scenarios show radical reductions in energy trade (to almost zero in one for the models in the ensemble - WITCH), whilst energy diversity rises to mid-century, then declines as renewables start to dominate. However, some regions’ dependence on imported oil could increase if unconventional sources are not exploited in mitigation scenarios. 34 Other impacts of mitigation options Other potential side-effects from the climate mitigation scenarios have been highlighted in the assessments reports such as IPCC 2014 [22]; these include biodiversity and land use changes, water consumption, employment. No precise assessments have been found in the projects analysed. Table 7: Secondary impacts of mitigation options Study / model / scenario Air quality details Energy security details Other EMF 27 BAU Not specified oil&gas: growing dependence on import + strong market concentration / primary energy: low diversification N/A EMF 27 450 Not specified oil&gas: reduced dependence N/A on import + marginal impact on diversity of suply / primary energy: increased diversification LIMITS FP7 Base Not specified large global trade FF / FF extract exceeds reserves / low diversity (transport) LIMITS FP7 450 ppm Not specified N/A low global trade FF (present level) / some FF left in ground /higher diversity (even in transport) RCP 2.6 NOx levels 60% of baseline (2050) Not given Land used for bioenergy increases from 3.9 million km2 in baseline to 9.3 million km2. Not given Bioenergy of >50 EJ/year by 2100 deemed possible by shifting towards food products with a smaller carbon footprint and reducing beef consumption. SO2 levels 20% of baseline (2050) RCP 4.5 Not specified N/A 35 RCP 6.0 NOx about 5-10% below baseline to 2060, then declines to about 25% below baseline by 2100. Not given No significant change in bioenergy usage in the scenario relative to the baseline. SO2 about 5-10% below baseline to 2060, then declines to about 50% below baseline by 2100. RoSE Not specified N/A 450ppm scenarios show radical reductions in energy trade, energy diversity rises to mid-century, then declines However, some regions’ dependence on imported oil could increase if unconventional sources are not exploited 9. Current knowledge and data gaps The goal of this report is to summarise the characteristics of possible long-term transformation pathways of GHG emissions toward stabilisation of climate change below long-term temperature targets of around 2°C and 2.5°C. A large number of scenarios assessed in this report share some common themes: 1. mitigation to 2°C or below is possible but requires early action to keep costs down; 2. at least a 60–80% share of global primary energy will need to come from zero-carbon options by 2050; 3. the electricity sector in particular will need to be almost completely decarbonized by mid-century (low carbon shares of 75–100%); 4. achieving a complete decarbonisation of the electricity sector will require a full portfolio of technologies. In particular, BECCS will be needed to achieve negative emissions later in the decade and coal power without CCS will need to be completely phased out by 2050; 5. delays or removal of key technologies makes the requisite levels of mitigation harder to achieve and / or more costly. There are a number of areas where there are significant variations between models used and the comparisons between different studies are therefore challenging. Variations between models include differences in socio economic assumptions, technology constraints, for example build rate constraints, which are not explicitly reported in most cases despite 36 being crucial, and assumed level of energy efficiency improvements which are in most cases not explicitly modelled. It is not clear why some models do not solve when the target is stringent and what technology constraints are binding. It is noticeable that there are inconsistencies between models related to methodologies, availability and costs for technology development. The technical potential and costs for renewables or nuclear power are uncertain and hard to quantify. In the case of CCS, studies have focused on its availability as a technology, rather than on the specific challenges and processes to use CCS effectively, for example the feasibility of storage within regions, or transport to storage sites in other regions. Long infrastructure lifetimes mean that it takes decades to change energy systems; so immediate action is needed to avoid lock-in of invested capital into existing energy systems and associated infrastructure that is not compatible with longer climate targets. Lock-in is sometimes explicitly identified as a challenge but the consequences of having massive capacities of idle assets (such as political feasibility) have not as yet been fully explored. In general the studies analysed do not account for political and institutional constraints, which is a challenge for future modeling studies. Further, within the range of results analysed, scenarios are defined by either concentration, radiative forcing or temperature targets. Where possible it could be helpful for scenarios to focus more explicitly on temperature stabilisation rather than concentration or radiative forcing, as for example temperature stabilisation pathways may have a different emissions profile than the concentration stabilisation pathways particularly in allowing temporary overshoots in GHG concentrations. Global warming impacts including those on energy and land use systems can be critical for mitigation policy decisions (primary energy availability, energy demand under climate change, crop production, and afforestation) and should also be included in the model calculations producing the pathways where possible. GHG emission reductions are a source of possible co-benefits, which has not been quantified in monetary terms. These co-benefits include for example air quality, health benefits, sustainable development, and green employment. Finally, under higher levels of warming, systems such as the climate or the natural environment may be affected by large positive feedbacks that could trigger tipping points and extreme events. Taking into account these strong feedbacks and possible high damages from changing climate could be important for high-end scenarios such as, in general, the “business as usual” case used as a reference to calculate consumption losses due to climate mitigation policies. In most studies the baseline or BAU is assumed to see GDP grow continuously to 2100, unaffected by climate damages. There are also discrepancies in geographical representation between models used in the pathway studies. There is a potential large variation in efficiency and cost of mitigation policies between different countries within the same regional block. Representing in greater detail the intra-regional differences in economic or technical development within integrated assessment model regions would be beneficial for future studies. Even though introduced in some projects (in AMPERE and EMF27), energy efficiency improvements are usually treated as a single extra scenario without details in technology, costs and deployments in the same way that can be found for the supply side changes. For achieving stringent climate targets low energy intensity on the demand side is important enough to bring more focus on it within the pathway descriptions. 37 The final suggestion from this report would recommend considering the difference between spending resources on abatement today and investments today in new technology that will allow lower-cost abatement later, such as renewable investment versus research in CCS and geo-engineering. 10. Concluding points This report presents an assessment of recent studies examining greenhouse gas emission pathways that are compatible with limiting average global temperature rise to levels close to 2°C or at least below 2.5°C by 2100. Whilst the studies examined show some variation due to differing underlying assumptions in areas such as technology constraints and socioeconomic factors, strong commonalities could be found between the studies and the following key conclusions drawn: 1. Mitigation to 2°C or below still is possible; 2.5°C is easier to achieve and can accommodate delay in decision. 2. Early action and a full portfolio of low-carbon technologies are needed to keep costs down. 3. Delays or removal of key technologies makes mitigation harder and / or more costly, and in the case of some models and scenarios, results in more stringent temperature targets becoming unacahievable. 4. Strong decarbonisation of the electricity sector combined with an increase in electrification of energy end use are required to achieve stringent targets. 5. Rapid increases in energy efficiency significantly improve the feasibility, and reduce the cost, of mitigation. There are over 20 global energy systems/IAM models used in the studies reported in this report. Each model has its own strength and weakness. Each model has its own assumptions on various parameters relevant to the models, such as technology costs, degree of technology availability and constraints on technology deployment rates. Though all the models are focused on climate change mitigation policy, in order to meet targets of either 2°C or below 2.5°C, there are a number of areas where there is (sometimes significant) variation between models used, which makes comparisons between the different studies challenging: 1. Different studies use different socio-economic assumptions on population and GDP growth 2. Technology constraints are very often not explicitly stated in scenario descriptions, despite being crucial for the achievability of targets. 3. Assumed levels of energy efficiency not explicitly modelled, at least not to the detail of which technologies and measures are required on the demand side to achieve the stated rates of efficiency improvement. 38 4. Costs are often reported in different ways, with some studie focused on carbon prices, some on consumption or GDP losses in particular years, and some on cumulative discounted GDP losses. 5. The degree of lock-in of carbon-intensive energy assets under mitigation scenarios is sometimes identified, but the consequences of idle assets, in terms of economic costs as well as political economy effects, is most often not fully explored. 6. Important co-benefits of GHG emissions reductions are not quantified in monetary terms, which makes it difficult to understand the degree to which these might effectively offset mitigation costs. 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