1 November 15, 2016 Japan Pavilion COP22, Marrakech Evaluations on the emission reduction efforts of Nationally Determined Contributions (NDCs) in cost metrics Keigo Akimoto Systems Analysis Group Research Institute of Innovative Technology for the Earth (RITE)
2 International Comparison of the Emission Reduction Efforts for the NDCs
3 How to measure the comparability of efforts 3 The submitted NDCs include the targets of emissions reduction from different base years, CO2 intensity, and CO2 emission reductions from baseline (w/w.o. clear definition of baseline). We need to interpret them through comparable metrics to measure the efforts: Simple metrics (easily measurable and replicable) - Emissions reduction from the same base year etc. Advanced metrics (more comprehensive, but require forecasts) - Emission reduction ratios from baseline emissions - Emissions per unit of GDP etc. More advanced metrics (most comprehensive, but require modeling) - Energy price impacts - Marginal abatement cost (per ton of CO2) - Abatement costs as a share of GDP etc.
4 Employed indicators for measuring emissions reduction efforts 4 Indicators for emissions reduction efforts Framework Notes More advanced metrics Advanced metrics Simple metrics Emissions reduction ratio from base year (only for OECD countries or Annex I countries) Emissions per capita (only for non-oecd countries or non-annex I countries) CO2 intensity (GHG emissions per GDP) Emissions reduction ratio compared to BAU CO2 marginal abatement cost (carbon price) Retail prices of energy (electricity, city gas, gasoline, diesel) Emission reduction costs per GDP Compared to 2005 Compared to 2012 (or 2010) Absolute value Absolute value Improvement rate (compared to 2012 or 2010) Employing historical data of 2012 or 2010 for weighted average When baseline emissions are expected to stagnate, it is more relevant to simply compare the projected reduction rates (all the more since there are uncertainties regarding the BAU). This is why we use the reduction ratio compared to BAU for OECD countries only - on the other hand, such an approach would be irrelevant for countries where emissions are expected to grow substantially. For non-oecd countries, we adopt the absolute value of emissions per capita instead of the reduction ratio from base year. Reveals what level of CO2 emissions corresponds to what degree of economic activity It will be better to measure emission reduction efforts because the bias due to differences in economic growth rate can be removed compared with the indicator of emission reduction ratio from base year. The differences in economic growth etc. can be cancelled. This is a particularly relevant indicator to assess reduction efforts as it contains countries differences in terms of economic growth, energy savings efforts, abatement potential of renewables. While marginal abatement costs reflect the frontier effort, this indicator corresponds to the efforts made in the baseline as a whole. This indicator corresponds to the economy s capability to bear efforts for the whole reduction. Most countries use 2005 as their base year (as a matter of fact, 1990 seems too far in the past to be used as a base year to evaluate the emissions reduction effort for upcoming emissions) Adopting a recent base year may enable appropriate comparison of future efforts. As this indicator (absolute value) is very dependent on country s situations such as economic development stage, industry structure, climate etc., not appropriate to measure reduction efforts. It can easily reach bad values for countries with a low GDP; it is also highly dependent on the country s industry structure. The value may change greatly for low GDP countries with high GDP growth rate. Efforts already made in the past for energy saving etc. are neglected and future abatement potential as well. Past efforts made for energy saving etc. may lead to high marginal abatement costs for additional reduction efforts. Market data is available for ex-post evaluation, but for ex-ante evaluation, only model-based estimates are available which makes uncertainties rather high. Uncertainties are high as this is a model-based estimation.
5 International comparison of emission reduction ratios in 2030 (in 2025 for the U.S.) from the base year of Switzerland Norway EU28 Canada New Zealand United United States States (2025) Australia Japan Korea Russia -EU countries) Belarus Kazakhstan Thailand Ukraine Mexico South Af rica China Turkey India East Europe(Non-EU countries) GHG emission compared to base year (2005) (%) * The average values are shown for the countries submitted the NDC with the upper and lower ranges larger smaller It is not easy to measure emission reduction efforts by using the emission reduction ratios from a certain base year due to large differences across countries in future economic growth and historical achievements of energy saving and emission reductions, for example.
6 International comparison of GHG emissions per GDP in 2030 (in 2025 for the U.S.) 6 Switzerland Norway Japan EU28 United United States States (2025) Canada Australia New Zealand Korea Mexico Turkey East Europe (Non-EU Thailand Russia China South Af rica Belarus Kazakhstan India Ukraine East Europe(Non-EU countries) GHG emission per GDP (kgco2eq/$2005) * The average values are shown for the countries submitted the NDC with the upper and lower ranges smaller larger GHG emission per GDP indicates economic efficiency of GHG emission in general, but it depends on the industrial structures and low-carbon energy supply potentials.
7 International comparison of CO 2 marginal abatement costs in 2030 (in 2025 for the U.S.) (RITE DNE21+ model) 7 Switzerland Japan EU28 Canada Korea New Zealand United United States States (2025) Norway ast Europe (Non-EU Thailand Australia Mexico Kazakhstan Belarus Russia South Africa Turkey India Ukraine China East Europe(Non-EU countries) bigger smaller CO2 marginal abatement cost ($/tco2) * The average values are shown for the countries submitted the NDC with the upper and lower ranges. Large differences in marginal abatement costs are estimated across countries. The large differences raise concern about inducing the carbon leakage and the ineffectiveness of global emission reductions.
8 International comparison of emission reduction costs per GDP in 2030 (in 2025 for the U.S.) (RITE DNE21+ model) 8 Australia Ukraine Thailand New Zealand East Europe (Non-EU Switzerland Korea EU28 Japan Canada United United States States (2025) South Africa Mexico Belarus Russia Turkey India Kazakhstan China Norway East Europe(Non-EU countries) Emission reduction cost per GDP (%) * The average values are shown for the countries submitted the NDC with the upper and lower ranges. Note: The emission reduction costs include the net cost changes due to changes of energy import and export. This indicator considers the economy s capability of emission reductions bigger smaller
9 Marginal abatement costs estimations across models (RITE DNE21+, FEEM WITCH and NIES AIM) Only energy-related CO2 emission reductions in 2030 CO2 marginal abatement cost (US$2005/tCO2) DNE21+ AIM/Enduse DNE21+ The average between 2025 and 2030 for GHG emission recutions WITCH DNE21+ WITCH DNE21+ WITCH DNE21+ WITCH DNE21+ WITCH USG Social Cost of Carbon (SCC): 53$/tCO2 for Marginal abatement costs if the aggregated NDCs are achieved most costefficiently: 16$/tCO2 by WITCH, 6$/tCO2 by DNE21+ Japan U.S. EU China India Korea/S.Africa/Australia Source: B. Pizer, J. Aldy, R. Kopp, K. Akimoto, F. Sano, M. Tavoni, COP21 side-event; MILES project report for Japan - The marginal abatement costs vary across models for some countries, but can be comparable for many countries/regions. -The CO2 marginal abatement costs of the NDCs of OECD countries are much higher than the marginal cost for the case that the aggregated NDCs are achieved most cost-efficiently (globally uniform marginal abatement cost).
10 Consideration of country's political and social situations in evaluation of the cost metrics 10 Cost metrics are comprehensive and good indicators for measuring emission reduction efforts, but How should we estimate the emission reduction costs more appropriately as the comparability metrics for measuring the efforts of NDCs? What are the inevitable social and political constraints for implementing climate policies? How should we treat the considerations of social and political constraints, e.g., nuclear power social acceptance, energy security issues, in the model analyses?
11 More Detailed Analysis on Japan s NDC
12 2030 Emission Target of Japan s NDC 12 Under the situations after the Great East Japan Earthquake and the Fukushima nuclear power accident, in 2014 the Japanese Government decided a new strategic energy plan which seeks a better balance of S+3E (safety, energy security, economy, and environment) and to reduce nuclear power plants. The energy mix for 2030 based on the strategic energy plan and the Japan s NDC which is consistent with the energy mix were decided in Energy-related CO2 Other GHGs Reduction by absorption Total GHGs 2030; Compared to 2013 compared to % -20.9% -1.5% -1.8% -2.6% -2.6% -26.0% -25.4% Energy-related CO2 by sector Industry Commercial and other Residential Transport Energy conversion Energy-related CO2 Total Unit: Mt-CO2
13 Japan s energy mix in 2030 Electricity mix 13 The Japanese government, July 2015 The government intends to reduce the dependence on nuclear power as compared with that before the accident. However, the government had to also take the 3E: energy security, economic efficiency, environment into account, and consequently the share of nuclear power is decided to be 20-22% of total electricity in I believe that this maintains a good balance of electricity mix in Japan.
14 The analysis cases for Japan s NDC GHG emis. target Energy related CO2 emission target Electricity share Fossil fuel [A0] GHG target + Level 2 energy mix -26% [A] Cost min. Coal: 26% LNG: 27% Oil: 3% (The same as the case assumed for the international comparison in previous slides) [B0] CO 2 target + Level % Coal: 26% energy mix LNG: 27% [B] Oil: 3% [B1] CO 2 target + Level 0 energy mix (The highest consistency with the specific measures listed in the Japan s NDC) [B2] CO 2 target + Level 1 energy mix [B3] CO 2 target + Level 3 energy mix (coal 26% + nuclear 20%) [B4] CO 2 target + Level 4 energy mix (nuclear 20%) [B5] CO 2 target + cost min. energy mix (Level 5) % Coal: 26% LNG: 27% Oil: 3% % Coal: 26% LNG: 27% Oil: 3% % Coal: 26% LNG: cost min. Oil: cost min. Note: Higher level of energy mix provides more flexibility. Nuclear power Renewables 20% 24% (cost min. within renewable sources) 20% 24% (cost min. within renewable sources) 20% 24% (PV: 7%, wind: 1.7% etc.) 20% 24% (cost min. within renewable sources) w./w.o. CCS option Cost min. Cost min. w.o. CCS w.o. CCS 20% Cost min. Cost min % Cost min. 20% Cost min. Cost min % Cost min. Cost min. Cost min. Cost min. 14 Electricity saving Cost min. Cost min. Total elec. Supply: 1065 TWh/yr Cost min. Cost min. Cost min. Cost min.
15 Evaluations of Japan s NDC in Electricity in Energy-related CO2 target: -21.9% Solar PV Wind power Nuclear power Hydro and Geothermal Biomass (w/ CCS) Biomass (w/o CCS) Gas power (w/ CCS) Gas power (w/o CCS) Oil power (w/ CCS) Oil power (w/o CCS) Coal power (w/ CCS) Coal power (w/o CCS) Estimated by RITE DNE21+ model The highest consistency with the specific measures listed in the Japan s NDC [B1] Energy-related CO2 target (-21.9%) [B1] CO2 target + Level + 0 Level energy 0 mix energy mix [B2] Energy-related CO2 target (-21.9%) [B2] CO2 target + Level 1 energy mix + Level 1 energy mix The same as the case assumed for the international comparison in previous slides [B0] Energy-related CO2 target (-21.9%) [B0] CO2 target + Level 2 energy mix + Level 2 energy mix [B3] CO2 target [B3] + Level 3 energy 3 energy mix mix (coal 26%+nuclear (coal + nuclear 20%) 20%) [B4] CO2 target + Level 4 energy [B4] Level 4 energy mix (nuclear 20%) mix (nuclear 20%) [B5] CO2 target + cost min. energy [B5] Cost min. energy mix mix (Level 5) Electricity generation [TWh/yr]
16 Evaluations of Japan s NDC in Mitigation Cost in [A0] GHG target (-26%) + Level 2 energy mix [B0] CO 2 target (-21.9%) + Level 2 energy mix Marginal abatement cost of CO2 ($2000/tCO2) The same as the case assumed for the international comparison in previous slides [B1] CO 2 target (-21.9%) + Level 0 energy mix The highest consistency with the listed specific measures in the Japan s NDC [B2] CO 2 target (-21.9%) + Level 1 energy mix [B3] CO 2 target (-21.9%) + Level 3 energy mix (coal 26% + nuclear 20%) [B4] CO 2 target (-21.9%) + Level 4 energy mix (nuclear 20%) [B5] CO 2 target (-21.9%) + cost min. energy mix (Level 5) Mitigation cost increase (billion $2000/yr) Mitigation cost increase per reference GDP (%) Which constraints should we consider as appropriate? Estimated by RITE DNE21+ model 4.1% GHG reductions by nonenergy CO2 is much more expensive than 21.9% GHG reductions by energy related CO2 Energy-related CO2 target (-21.9%) Electricity saving target etc. Renewable energy target etc. Considering energy security issue Considering social constraint of nuclear power Note: it should be noted that the orders of between marginal cost and mitigation cost are different. The constraints for specific measures could reduce the CO2 marginal abatement cost while total mitigation cost increases.
17 Sensitivity to the mitigation measure options (For energy-related CO2 target (-21.9%) case) 17 With CCS ( Level 2 energy mix) Mitigation cost increase per reference GDP (%) Without CCS (Level 1 energy mix) The same as the case assumed for the international comparison in previous slides [B0] CO2 target + Level 2 energy mix 0.40 [B3] CO2 target + Level 3 energy mix (coal 26% + nuclear 20%) 0.34 [B4] CO2 target + Level 4 energy mix (nuclear 20%) 0.28 [B5] CO2 target + cost min. energy mix (Level 5) 0.15 More specific renewable energy target [B2] CO2 target + Level 1 energy mix 0.46 Renewable energy target Considering energy security issue Considering social constraint of nuclear power Without CCS + Electricity savings (Level 0 energy mix) [B1] CO2 target + Level 0 energy mix 0.55 The highest consistency with the listed specific measures in the Japan s NDC Larger constraints of mitigation measures of CCS and electricity savings Larger constraints of energy mix for renewables, fossil fuel, and nuclear power Estimated by RITE DNE21+ model
18 More Detailed Analysis on the U.S. s NDC
19 Consideration of Clean Power Plan (CPP) 19 The U.S. submitted 26-28% reduction of GHG in 2025 relative to 2005 as her NDC. The U.S. will achieve the target by introducing domestic climate policies including the Clean Power Plan (CPP). How does the CPP affect the emission reduction costs? GHG emission reduction estimates by policy Assessment of the emission reduction effect of CPP by the U.S. EPA (million tco2/yr) Rate-based approach Mass-based approach Source: US EPA, 2015 Source: J.B. Greenblatt and M. Wei, Nature Climate Change, 2016
20 CO2 emissions by sector in 2025 (-28% case) The U.S. target: GHG -28% relative to 2005 Residential & Commercial Transportation Industry Other energy conversion Electricity generation 2005 Baseline 2025 Carbon intensity of CPP w.o. additional elec. saving (w.o. CCS) The highest consistency with the CPP Carbon intensity of CPP w.o. additional elec. saving (with CCS) Carbon intensity of CPP with additional elec. saving (w.o. CCS) Least cost measure (w/o CCS) Least cost measure The same as the case assumed for the international comparison in previous slides Energy-related CO2 emission [MtCO2/yr] * * The emission reduction in power sector: about 270 MtCO2/yr Large reductions in other sectors than power sector are required. Estimated by RITE DNE21+ model * Considering the electricity savings only due to the electricity price increase induced by the CPP
21 Electricity generation in 2025 (-28% case) Net Import Solar PV Wind power Nuclear power Hydro and Geothermal Biomass (w/ CCS) Biomass (w/o CCS) Gas power (w/ CCS) 2005 Baseline 2025 Carbon intensity of CPP w.o. additional elec. saving (w.o. CCS) The highest consistency with the CPP Carbon intensity of CPP w.o. additional elec. saving (with CCS) Carbon intensity of CPP with additional elec. saving (w.o. CCS) Least cost measure (w/o CCS) Least cost measure The same as the case assumed for the international comparison in previous slides Electricity generation [TWh/yr] Gas power (w/o CCS) Oil power (w/ CCS) * * Estimated by RITE DNE21+ model * Considering the electricity savings only due to the electricity price increase induced by the CPP Oil power (w/o CCS) Coal power (w/ CCS) Coal power (w/o CCS)
22 Evaluations of the U.S. s NDC in Mitigation Cost in GHG targe t (%) -28% -26% [A1] Carbon intensity of CPP (w.o. CCS) w.o. additional elec. saving [A2] Carbon intensity of CPP (with CCS) w.o. additional elec. saving [A3] Carbon intensity of CPP with additional elec. saving [A4] The least cost measures (but w.o. CCS) Marginal abatement cost of CO2 ($2000/tCO2) Mitigation cost increase (billion $2000/yr) Mitigation cost increase per reference GDP (%) [A5] The least cost measures [B1] Carbon intensity of CPP (w.o. CCS) w.o. additional elec. saving [B5] The least cost measures Estimated by RITE DNE21+ model The highest consistency with the CPP The same as the case assumed for the international comparison in previous slides - If the mitigation measures of power sector under the Clean Power Plan (CPP) are imperative, the mitigation costs are extremely large for achieving the 28% reduction relative to 2005 because large emission reductions are required in other sectors than power sector. - There are large gaps in mitigation costs between the least cost measures and the realistic policy measures.
23 Conclusions 23 Measuring the emission reduction efforts (degree of ambition) of NDCs is key for effective emission reductions under the Paris Agreement. Measuring the efforts is a hard work but can be approached by employing multiple good indicators including the mitigation costs. Evaluations of the mitigation costs require comprehensive models and include uncertainties but using several models helps ensure comparability to some extent. Another challenging issue on evaluations of the mitigation costs is what constraints are inevitable and should be considered in estimating the mitigation costs. Several social and political conditions hindering the least cost mitigation measures exist in each nation. Cheaper emission reduction measures should be pursued, but some of the realistic constraints should also be considered. At least, we should recognize the existence of such conditions that may cause cost increase for each nation in the review process of NDCs for effective emission reductions.
25 Assumptions of Population and GDP for the Estimations of the Indicators and Overview of the Models for the Estimations of Costs
26 Population prospects (millions) Japan United States EU Switzerland Norway Australia New Zealand Canada Russia China Korea Mexico Ukraine Belarus Kazakhstan East Europe (Non-EU countries) Thailand India Turkey South Africa The World Total Source) RITE estimates based on the 2008 UN population prospects in the medium variants. For statistical values up to 2010, The UN World Population Prospects 2012 are used.
27 GDP Prospects (MER, %/yr) Japan United States EU Switzerland Norway Australia New Zealand Canada Russia China Korea Mexico Ukraine Belarus Kazakhstan East Europe (Non-EU countries) Thailand India Turkey South Africa The World Average Source) RITE estimates. Our estimates are not so different form USDOE/EIA International Energy Outlook and IEA World Energy Outlook. (In consideration of the differences between PPP and MER)
28 Overview of the RITE Model 28
29 Global Warming Mitigation Assessment Model (Dynamic New Earth 21+) 29 The emission reduction costs in this study were estimated by an energy and global warming mitigation measures DNE21+. Energy-related CO2 emission reduction costs can be estimated with consistency. Linear programming model (minimizing world energy system cost) Evaluation time period: Representative time points: 2000, 2005, 2010, 2015, 2020, 2025, 2030, 2040, 2050 World divided into 54 regions Large area countries are further divided into 3-8 regions, and the world is divided into 77 regions. Interregional trade: coal, crude oil, natural gas, electricity, ethanol, hydrogen, and CO2 Bottom-up modeling for technologies both in energy supply and demand sides (about 300 specific technologies are modeled.) Primary energy: coal, oil, natural gas, hydro, geothermal, wind, photovoltaics, biomass, nuclear power, and ocean energy End-use sector: bottom-up modeling for technologies in iron & steel, cement, paper & pulp, chemical, aluminum, and car, and some technologies in residential & commercial sectors, and top-down modelling for sectors without bottom-up modeling by using price elasticity The detailed assessments by region and by sector are possible with consistency. The assessments of DNE21+ model are referred in the IPCC AR5, and those have been referred also for the decision processes for climate change mitigation policy in Japanese government. [Reviewed articles (selected)] K. Akimoto et al.; Estimates of GHG emission reduction potential by country, sector, and cost, Energy Policy, 38 7, (2010) K. Akimoto et al.; Assessment of the emission reduction target of halving CO2 emissions by 2050: macro-factors analysis and model analysis under newly developed socio-economic scenarios, Energy Strategy Reviews, 2, 3 4, (2014)
30 Evaluations of Emission Reduction Efforts for the INDCs Submitted by Governments
31 Evaluated INDCs (1/2) 31 The 119 INDCs submitted as of October 1 st, 2015 were evaluated. As of October 1 st, 2015, 119 INDCs had been submitted, and representing about 88 per cent of global emissions in Comprehensive evaluations of emission reduction efforts were only for 20 countries (see below) due to the limited regional resolution of the model (Cancun Agreements) Post-2020 (INDCs) United States -17% compared to % to -28% by 2025 compared to 2005 Canada -17% compared to % by 2030 compared to 2005 EU28-20% compared to % by 2030 compared to 1990 Switzerland -20% compared to % by 2030 compared to % by 2025 compared to 1990 Norway -30% compared to % by 2030 compared to 1990 Japan -3.8% compared to 2005* -26% by 2030 compared to 2013 Australia -5% compared to % to -28% by 2030 compared to 2005 New Zealand -5% compared to % by 2030 compared to 2005 Russia -15 to -25% compared to % to -30% by 2030 compared to 1990 Note: More ambitious emission reduction targets had been submitted as conditional targets from some countries, but they are not included in this table. * Emission reduction target assuming zero nuclear power
32 Evaluated INDCs 2/ (Cancun Agreements) Post-2020 (INDCs) Non-EU Eastern Europe -19% by 2030 compared to 1990* Ukraine -20% compared to % by 2030 compared to BAU Belarus -5 to -10% compared to % by 2030 compared to 1990 Kazakhstan -15% compared to % by 2030 compared to 1990 Turkey -21% by 2030 compared to BAU Korea -30% compared to BAU -37% by 2030 compared to BAU Mexico -30% compared to BAU -25% by 2030 compared to BAU** (-22% by 2030 compared to BAU in GHG) South Africa -34% compared to BAU 614MtCO 2 eq/yr by 2030 Thailand -7 to -20% compared to BAU (Energy and transportation sectors) -20% by 2030 compared to BAU China India To reduce CO 2 /GDP by -40 to -45% compared to 2005 To reduce GHG/GDP by -20 to -25% compared to 2005 * The reduction rate was estimated from the total emissions by the INDCs of Albania, Makedonia, Moldova, and Serbia. ** Emission reduction target of Mexico includes black carbon. To reduce CO 2 /GDP by -60 to -65% by 2030 compared to 2005 (To achieve the peaking of CO 2 emissions around 2030 and making best efforts to peak early) To reduce GHG/GDP by -33 to -35% by 2030 compared to 2005
33 Notes of the assessments of INDCs in this study 33 LULUCF emissions are not taken into account for international comparison of mitigation efforts, because they have large uncertainty and their appropriate evaluation is difficult. (LULUCF emissions are taken into account for the aggregated INDCs evaluation with respect to 2 C target.) For the countries with emission reduction targets compared to the base year, the emissions in the target year are calculated based on historical emissions excluding LULUCF. Historical emissions are derived from Greenhouse Gas Inventory Office of Japan for Japan, UNFCCC for other Annex I countries, and IEA for other countries. For the countries with emission intensity improvements targets, the emissions in the target year are calculated based on historical emissions and our GDP scenario. For the countries with emission reduction ratio targets to BAU, if BAU emissions in target year are stated in their INDCs, the values of INDCs are adopted for calculation of emissions in the target year. If not, their INDCs are not evaluated in the international comparison of mitigation efforts in this study. (For the aggregated INDCs evaluation with respect to 2 C target, their carbon prices are assumed to be zero until 2030.) Other countries with policies and actions targets are omitted from this assessment. Most of the countries set 2030 as the target year, but the United States and Brazil chose For these countries, indicators concerning emission reduction efforts in 2025 are evaluated and compared with the other countries indicators in Evaluation of all of the adopted indicators was carried out for twenty regions. For Brazil and Indonesia who are large emitters from LULUCF, only the three indicators (emission reductions compared to base year, emissions per capita, and emissions per GDP) are evaluated including LULUCF.
34 Japan s Energy Mix in 2030
35 Japan s energy mix in 2030 final energy and primary energy mix 35 The Japanese government, July 2015 The energy mix was designed with the following three major objectives, plus the basic requirement of safety: 1) The self-energy sufficiency ratio should be required to be the same level as one before the earthquake (around 25%). 2) The electricity cost should be reduced compared to the current level. 3) Greenhouse gas emissions should be reduced as to make Japan a leading example for the rest of the world and the reduction efforts should be well compared with the EU s and the US s.
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