Hybrid Linking TIAM-KLEM: Assessing technological pathways from INDCs towards 1.5C James Glynn, Frédric Ghersi, Franck Lecocq,

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1 Hybrid Linking TIAM-KLEM: Assessing technological pathways from INDCs towards 1.5C James Glynn, Frédric Ghersi, Franck Lecocq, ERI-UCC, CIRED - IEW2016 Cork, IRELAND Brian Ó Gallachóir

2 Outline Research Question: How far below 2 C is feasible? (if at all?) What would the macroeconomic impacts, demand response and sectoral dynamics be? Presentation in two sections TIAM-MACRO How far below 2C towards 1.5C can we go? TIAM-KLEM Hybrid linking methods between KLEM and ETSAP-TIAM What we have done What we haven t done What we hope to do

3 Post Paris Policy Context COP21 Highlight figures. CP21, Article 2.1(a) Holding the increase in the global average temperature to well below 2 C above preindustrial levels and pursuing efforts to limit temperature increase to 1.5 C would significantly reduce risks and impacts of climate change AR5 carbon budget for the total global cumulative emissions since 2011 that are consistent with a global average temperature rise of 1.5C above pre industrial levels with 50% probability is 550GtCO 2. Considering the aggregate effect of INDCs, global cumulative CO 2 emissions are expected to equal 97% by 2025 and 134% by 2030 of the cumulative emissions consistent with achieving a temperature increase of less than 1.5 C INDCs result in ~52GtCO 2 e/yr in 2030 Not on a 2 C least cost consistent path

4 GLOBAL ETSAP-TIAM model Linear programming bottom-up energy system model of IEA-ETSAP Integrated model of the entire energy system Prospective analysis on medium to long term horizon (2100) Demand driven by exogenous energy service demands Partial and dynamic equilibrium (perfect market) Optimal technology selection Minimizes the total system cost Environmental constraints Integrated Climate Model 15 Region Global Model Price-elastic demands Macro Stand Alone Single consumer-producer, multi-regional, inter-temporal general equilibrium model which maximises regional utility. The utility is a logarithmic function of the consumption of a single generic consumer. Production inputs are labour, capital and energy. Energy demand and energy costs from ETSAP-TIAM model. MSA Re-estimates Energy Service Demands based on energy cost

5 Scenario Definitions Incremental Carbon Budgets from 1400GtCO 2-400GtCO 2 Climate model controlling concentrations of CH 4 and N 2 0 for 2 C in 2100 Delaying action where feasible 2010, 2020, 2030, 2040 Find the feasible solution space in AR5 carbon budgets between 2 C and 1.5 C AR5 all working group Synthesis Report Table 2.2 <1.5C <2C >3.5C Carbon Budget GtCO2 66% 50% 33% 66% 50% Start Year/ Delayed Action Base 2005 <1.5C 66% <1.5C 50% <1.5C 50% <1.5C 50% <1.5C 33% <1.5C 33% <1.5C 33% <1.5C 33% <2C 66% <2C 50% <2C 50% 4DS MACRO RUNS 2010 <1.5C 66% <1.5C50% <1.5C50% <1.5C50% <1.5C 33% <1.5C 33% <1.5C 33% <1.5C 33% <2C 66% <2C 50% <2C 50% 2020 <1.5C 66% <1.5C50% <1.5C50% <1.5C50% <1.5C 33% <1.5C 33% <1.5C 33% <1.5C 33% <2C 66% <2C 50% <2C 50% 2030 <1.5C 66% <1.5C50% <1.5C50% <1.5C50% <1.5C 33% <1.5C 33% <1.5C 33% <1.5C 33% <2C 66% <2C 66% <2C 50% 2040 <1.5C 66% <1.5C50% <1.5C50% <1.5C50% <1.5C 33% <1.5C 33% <1.5C 33% <1.5C 33% <2C 66% <2C 66% <2C 50%

6 CO2 (ONLY) (Gt/yr) CO2 Trajectories BASE_0 Historical FFI 2DS_CM_1400GtCO2 2DS_CM_1400GtCO2_DA10 2DS_CM_1400GtCO2_DA10_MSA 2DS_CM_1400GtCO2_DA30 2DS_CM_1400GtCO2_DA20_MSA 2DS_CM_1300GtCO2 2DS_CM_1300GtCO2_DA10 2DS_CM_1300GtCO2_DA20 2DS_CM_1000GtCO2 2DS_CM_1000GtCO2_DA10 2DS_CM_900GtCO2 2DS_CM_850GtCO2 2DS_CM_800GtCO2 2DS_CM_700GtCO2 2DS_CM_600GtCO2 2DS_CM_550GtCO2 2DS_CM_500GtCO2-20 Years

7 Temperature Change ( C) How low (<2 C) can we go? 1.5C Temperature threshold or 2100 Target 4 BASE_0_CM DS_CM_1400GtCO2 2DS_CM_1400GtCO2_DA10 2DS_CM_1400GtCO2_DA10_MSA 2DS_CM_1400GtCO2_DA30 2DS_CM_1400GtCO2_DA20_MSA 2DS_CM_1400GtCO2_DA40 2DS_CM_1300GtCO2 2DS_CM_1300GtCO2_DA10 2DS_CM_1300GtCO2_DA20 2DS_CM_1300GtCO2_DA30 2DS_CM_1000GtCO2 2DS_CM_1000GtCO2_DA10 2DS_CM_1000GtCO2_DA20 2DS_CM_1000GtCO2_DA30 2DS_CM_900GtCO2 2DS_CM_850GtCO2 2DS_CM_800GtCO2 2DS_CM_700GtCO2 2DS_CM_600GtCO2 2DS_CM_550GtCO2

8 Temperature Change ( C) Temperature Change 1.5C Threshold or 2100 Target BASE_0_CM 2DS_CM_1400GtCO2_DA30 2DS_CM_1400GtCO2_DA20_MSA 2DS_CM_1400GtCO2_DA40 2DS_CM_1300GtCO2_DA20 2DS_CM_1300GtCO2_DA30 2DS_CM_1000GtCO2_DA

9 Marginal Abatement Cost ($2005/tCO2 Marginal Abatement costs break by starting year DS_CM_1400GtCO2 2DS_CM_1300GtCO DS_CM_900GtCO2 2DS_CM_850GtCO2 2DS_CM_800GtCO DS_CM_700GtCO2 2DS_CM_600GtCO DS_CM_550GtCO2 2DS_CM_500GtCO2 2DS_CM_400GtCO DS_CM_1400GtCO2_DA10 2DS_CM_1300GtCO2_DA10 2DS_CM_1000GtCO2_DA DS_CM_1400GtCO2_DA20 2DS_CM_1300GtCO2_DA DS_CM_1400GtCO2_DA30 2DS_CM_1400GtCO2_DA40

10 2DS 66% Energy System in ,000 GtCO 2 Budget

11 Primary Energy Supply (Mtoe) Primary Energy Supply 30,000 25,000 20,000 15,000 10,000 5,000-4DS. 4DS 2DS 50% 2DS 50% DA30 2DS 66%. 4DS 2DS 50% 2DS 50% DA30 2DS 66%. 4DS 2DS 50% 2DS 50% DA30 2DS 66%. 4DS 2DS 50% Coal Oil Gas Nuclear Hydro Biomass Renewable except hydro and biomass 2DS 50% DA30 2DS 66%

12 Electricity Capacity (GW) Power System production 30,000 25,000 20,000 15,000 10,000 Solar PV Solar Thermal Wind Geo and Tidal Biomass CCS Biomass Hydro Nuclear Gas and Oil Coal 5,000-4DS. 4DS 2DS 50% 2DS 50% DA30 2DS 66%. 4DS 2DS 50% 2DS 50% DA30 2DS 66%. 4DS 2DS 50% 2DS 50% DA30 2DS 66%. 4DS 2DS 50% DS 50% DA30 2DS 66%

13 GDP losses & Delayed Action 2DS 50% DA20 2DS 50% Former Soviet Union 2DS 50% DA20 Australia & NZ South Korea Other Developing Asia 2DS 50% Canada Middle East China 2DS 50% DA20 East Europe Africa India 2DS 50% West Europe Japan USA 2DS 50% DA20 Central South America Mexico 2DS 50% GDP Loss %

14 The KLEM model and its linkage to TIAM Frédéric Ghersi (CNRS/CIRED)

15 Why Hybrid Linking? Update TIAM Macroeconomic outlook(s) Harmonisation of energy service demands with changing economic outlook. Aim for Best of both worlds. Technological Explicitness Macroeconomic realism Sectoral Dynamics (Energy, Non Energy, Households) Demand response (adaptation) is critical to meet deep decarbonisation scenarios. Moving forward from TIAM-MACRO Investigate multi-sector dynamics Better represent socio-economic dynamics

16 Overview of linkage TIMES-MACRO (Remme & Blesl, 2006) Simultaneously TIAM-KLEM Labour Energy p&qs Households consumption TIAM ES investment Non-E output KLEM Public consumption International trade Investment?Non-E prices? Iteratively Non-E/E Capital

17 Prerequisites National accounting framework to access Complete cost structures K, L, E, M (1,,n) Inter-industry flows i.e. structural change, dematerialisation Market instruments recycling options Distributive issues, at least firms/government/households Dual accounting in monetary and physical units To keep track of energy volumes in stand-alone versions To model agent-specific pricing Explicit investment profiles To account for transitional strain on shorter time intervals

18 KLEM at a glimpse CGEM with 2 primary factors L and K, 1 E good, 1 non-e good Recursive dynamics driven by Exogenous L supply and productivity (SSP) K accumulation via exogenous investment & depreciation rates Public expenses constant share of GDP, constant (rough) tax system Operates on hybrid energy/economy matrix obtained from crossing GTAP and TIAM data 18/16

19 Base year (2007) IOT, WEU B$ Non-E E C G I X Uses Non-E E L net L taxes Y taxes K M SM non-e SM E SM C SM X Sales taxes Resources

20 Base year (2007) IOT, WEU B$ Non-E E C G I X Uses Non-E E L net L taxes Y taxes K M SM non-e SM E SM C SM X Sales taxes Resources E uses and imports are TIAM data with explicit p x q decomposition

21 Base year (2007) IOT, WEU B$ Non-E E C G I X Uses Non-E E L net L taxes Y taxes K M SM non-e SM E SM C SM X Sales taxes Resources E uses and imports are TIAM data with explicit p x q decomposition Remainder of E resource structure scaled up/down from GTAP to balance uses

22 Base year (2007) IOT, WEU B$ Non-E E C G I X Uses Non-E E L net L taxes Y taxes K M SM non-e SM E SM C SM X Sales taxes Resources E uses and imports are TIAM data with explicit p x q decomposition Remainder of E resource structure scaled up/down from GTAP to balance uses Calibrated zero-sum specific margins warrant agent-specific E prices

23 Base year (2007) IOT, WEU B$ Non-E E C G I X Uses Non-E E L net L taxes Y taxes K M SM non-e SM E SM C SM X Sales taxes Resources Non-E data deduced from GTAP totals

24 KLEM behavioural assumptions Output sequential trade-off of K vs. L then KL vs. E then KLE vs. M (aggregate of non-e goods) K vs. L, KLE vs. M settled by CES functions KL (VA) vs. E from TIAM under a maintained CES assumption for KLE Aggregate savings rate exogenous (recursive dynamics) Households E consumption from TIAM International trade E trade from TIAM Non-E trade: ratio of M to Y isoelastic to terms of trade; X settled by international good CES of exported goods (Armington) 24/16

25 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E E ### ### ### - - ### ### L net L taxes Y taxes K ### M ### SM non-e SM E SM C SM X Sales taxes Resources TIAM trajectory prescribes E uses and imports as well as E investment requirements, which drive K E accumulation K rental price adjusts to balance remainder of K supply and K demand by non-e production

26 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E E ### ### ### - - ### ### L net ### L taxes ### Y taxes K ### M ### SM non-e SM E SM C SM X Sales taxes Resources Labour intensity of E production assumed constant, wage adjusts to balance remainder of L supply and L demand by non-e production Optional imperfect L market magnifies cost of E investment crowding out non-e investment

27 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E ### E ### ### ### - - ### ### L net ### L taxes ### Y taxes 649 ### K ### M ### SM non-e SM E SM C SM X Sales taxes ### Resources M (non-e) intensity of E production trades off with KLE aggregate under a constant elasticity of substitution assumption Output and sales taxes constant ad valorem rates

28 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E ### E ### ### ### - - ### ### L net ### L taxes ### Y taxes 649 ### K ### M ### SM non-e - ### SM E - ### SM C - ### SM X - ### Sales taxes ### Resources ### Specific margins adjust to have E end-use prices match TIAM agentspecific prices

29 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E ### E ### ### ### - - ### ### L net ### ### L taxes ### ### Y taxes 649 ### K ### ### M ### SM non-e - ### SM E - ### SM C - ### SM X - ### Sales taxes ### Resources ### In non-e production K and L trade off with constant elasticity to produce aggregate KL (VA) considering wage and rent adjusted to clear markets Optional imperfect L market magnifies cost of E investment crowding-out non-e investment Resulting K, L and E combine into aggregate KLE following CES specification

30 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E ### ### E ### ### ### - - ### ### L net ### ### L taxes ### ### Y taxes 649 ### K ### ### M ### SM non-e - ### SM E - ### SM C - ### SM X - ### Sales taxes ### Resources ### In non-e production Non-E intensity of non-e production and KLE aggregate trade off to produce domestic output Y The price of the non-e good is the weighted average of domestic and import prices

31 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E ### ### E ### ### ### - - ### ### L net ### ### L taxes ### ### Y taxes 649 ### K ### ### M ### ### SM non-e - ### SM E - ### SM C - ### SM X - ### Sales taxes ### Resources ### In non-e production The ratio of imports to domestic output in (volumes) is isoelastic to the ratio of their prices

32 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E ### ### E ### ### ### - - ### ### L net ### ### L taxes ### ### In non-e production Y taxes ### ### Exogenous tax rates K ### ### M ### ### SM non-e - ### SM E - ### SM C - ### SM X - ### Sales taxes 1 ### ### Resources ###

33 At each period from 2010 to 2100 B$ Non-E E C G I X Uses Non-E ### ### ### ### ### ### ### E ### ### ### - - ### ### L net ### ### L taxes ### ### Y taxes ### ### K ### ### M ### ### SM non-e - ### SM E - ### SM C - ### SM X - ### Sales taxes 1 ### ### Resources ### ### Final non-e consumptions G and I are exogenous shares of GDP X trades off with Xs of other regions at constant elasticity of substitution (Armington) to provide sum of Ms Closure of accounting balance defines C

34 Overview of linkage TIMES-MACRO (Remme & Blesl, 2006) Simultaneously TIAM-KLEM Labour Energy p&qs Households consumption TIAM ES investment Non-E output KLEM Public consumption International trade Investment?Non-E prices? Iteratively Non-E/E Capital

35 Conclusions Achieving below 2C is highly improbable and near infeasible. 1.9 C 1.8 C simple climate model GDP losses in the utility maximising least cost scenario for delayed action to 2020 is regionally varied and inequitable. Greater structural resolution and flexibility is required in hybrid models to better account for limits to substation and structure change. This hybrid type of approach steps towards sectoral specific dynamics of decarbonising from a bottom up technology explicit perspective Unemployment, structural changes, sectoral outputs Could inform targeted regional/sector specific transition policies

36 Acknowledgements Centre International de Recherche sur l Environnement et le Développement

37 Environmental Research Institute Instiúd Taighde Comshaoil Energy Policy and Modelling Group