Carbon Emission Scenarios for Future China

Transcription

1 Carbon Emission Scenarios for Future China Wenying Chen Institute of Energy Environment and Economy (3E) Tsinghua University Nov. 15, 214

2 Energy system optimization model: China MARKAL/TIMES Dynamic linear programming model based on Reference Energy System(RES). Incorporate the full range of energy processes e.g. exploitation, conversion, transmission, distribution and end-use. Consider existing technologies as well as advanced technologies which may be deployed in future. Searche for a least-cost combination of technologies and fuels dynamically over the planning period to meet user-specified energy service demands.

3 Main inputs and outputs Technology Characteristics Energy Sources Used Efficiency Costs (Capital and O&M) Availability Energy Source Data Cost Availability Dynamic LP Optimization Energy Demands By Sector Other Assumptions Long-Term Discount Rate Other Constraints Max. CO 2 Emissions by Time Period Technology Mix for Each Time Period That Satisfies Energy Demand Given System Constraints Carbon emission scenarios

4 Key social-economic drivers for future carbon emission growth: GDP ERI IEA LBNL UNDP EIA_REF EIA_H EIA_L HSBC 3E/TU na na na na

5 Key social-economic drivers for future carbon emission growth: industrial structure % % % 46.75% 1.1% % 45.77% 7.8% % 44.36% 5.53% % Primary Secondary Tertiary 41.21% 3.58% 38.38% 2.55% 36.31% 2.3%

6 Key social-economic drivers for future carbon emission growth: Population and urbanization

7 How social economic drivers to impact energy service demand Industry Energy-intensive products Others Transport Freight transport (Air, railway, highway, waterway, pipeline) Passport transport (Air, railway, highway, waterway) Building Space heating Cooking and water heating Cooling Lighting and electric appliances

8 Energy service demand projection model

9 Steel demand projection approach

10 Steel demand projection

11 Sensitivity analysis of future steel demand

12 Building floor space projection

13 Building ESD projection Heating/EJ commercial rural urban SC C HSCW HSWW Cooling/EJ commercial rural urban SC C HSCW HSWW hotwater & cooking/ej commercial rural urban SC C HSCW HSWW Lighting/PJ commercial rural urban SC C HSCW HSWW

14 Transportation ESD projection Passenger service demand (bn pkm) INTL_AIR RURAL BUSINESS INTERCITY URBAN Freight service demand (bn tkm) Pipeline Rural 3W&4W INTL_SHIP INTL_AIR DOM_SHIP DOM_AIR DOM_RAIL DOM_ROAD

15 Scenarios (without elastic demand) Reference C3534 C3535 C35354 C35355 C3544 C3545 C444 C44545 C455 C4544 C C Other Ocean Geothermal Solar Wind Nuclear Hydro Biomass w/ CCS Biomass w/o CCS Gas w/ CCS Gas w/o CCS Oil w/ CCS Oil w/o CCS Coal w/ CCS Coal w/o CCS CO2 emission/mt Reference Reference Reference C3534 C3535 C35354 C35355 C3544 C3545 C444 C44545 C455 C4544 C C4555 Reference C3534 C3535 C35354 C35355 C3544 C3545 C444 C44545 C455 C4544 C C4555 Reference C3534 C3535 C35354 C35355 C3544 C3545 C444 C44545 C455 C4544 C C4555 Primary energy consumption/ej Biomass Non-biomass renewables Nuclear CCS Fuel switch End-use efficiency improvement reference carbon emission Carbon emission/gt CO C4555 carbon emission Reference Reference Reference C3534 C3535 C35354 C35355 C3544 C3545 C444 C44545 C455 C4544 C C4555 Reference C3534 C3535 C35354 C35355 C3544 C3545 C444 C44545 C455 C4544 C C4555 Reference C3534 C3535 C35354 C35355 C3544 C3545 C444 C44545 C455 C4544 C C Other Geothermal Solar Wind Nuclear Hydro Biomass w/ CCS Biomass w/o CCS Gas w/ CCS Gas w/o CCS Oil w/ CCS Oil w/o CCS Coal w/ CCS Coal w/o CCS Primary energy/ej

16 Scenarios (with elastic demand) REF M1 M2 M3 M4 Carbon emission/mton REF REF M1 M2 M3 M4 -- REF M1 M2 M3 M4 REF M1 M2 M3 M4 REF M1 M2 M3 M Primary energy consumption/mtce 3 CO2 mitigation resulted from ESD reductions/mt 3 CO 2 mitigations/mt M1 M2 M3 M4 M1 M2 M3 M4 M1 M2 M3 M4 M1 M2 M3 M4 M1 M2 M3 M4 M1 M2 M3 M4 M1 M2 M3 M4 M1 M2 M3 M4 3 CO 2 mitigation resulted from ESD reductions/mt 12 CO 2 mitigations/mt Primary energy consumption Other Wind Solar Nuclear Hydro Biomass Natural gas w/ CCS Natural gas w/o CCS Oil w/ CCS Oil w/o CCS Coal w/ CCS Coal w/o CCS Building Transportation Industry Agriculture Building Transportation Industry Agriculture PF_M1 PF_M2 PF_M3 PF_M4 PF_M1 PF_M2 PF_M3 PF_M4 PF_M1 PF_M2 PF_M3 PF_M4 PF_M1 PF_M2 PF_M3 PF_M4 PF_M1 PF_M2 PF_M3 PF_M4 PF_M1 PF_M2 PF_M3 PF_M4 PF_M1 PF_M2 PF_M3 PF_M4 PF_M1 PF_M2 PF_M3 PF_M4

17 Comparison with other domestic studies

18 Model comparisons GCAM (Global Change Assessment Model) developed by the Joint Global Change Research Institute, USA IPAC (Integrated Policy Assessment Model for China) developed by the Energy Research Institute, China REMIND (Refined Model of Investments and Technological Development) developed by the Potsdam Institute for Climate Impact Research, Germany WITCH (World Induced Technical Change Hybrid) developed by the Centro Euro-Mediterranean Centre on Climate Change, Italy

19 Model comparisons Model China TIMES GCAM IPAC REMIND WITCH Region Global Global Global Global China coverage (14 regions) (9 regions) (11 regions) (13 regions) Time Horizon Recursive Recursive Inter-temporal Inter-temporal Energy system dynamic, dynamic, optimization, optimization, Model class optimization, partial partial general general partial equilibrium equilibrium equilibrium equilibrium equilibrium End-use sectors 6 (agriculture, industry, transportation, commercial, urban, rural), further divided into 43 subsectors 3 (industry, transportation, building) 3 (industry, transportation, building) 2(transportation, other) 1 aggregated Demands Exogenous energy service demands Endogenous energy service demand driven by income and price Endogenous energy service demand driven by income and price Endogenous CES production function Endogenous CES production function Technology choice by Endogenous learning Endogenous R&D Linear least-cost Logit-shares based on cost Logit-shares based on cost Inter-temporal cost minimization Inter-temporal cost minimization No No No Yes Yes No No No No Yes

20 Model comparisons for reference scenarios CO2 emission/mt TIM ES Reference GCAM_BAU DEF IPAC_BAU DEF REMIND_BAU DEF WITCH_BAU DEF Primary energy consumption/ej Other Ocean Geothermal Solar Wind Nuclear Hydro Biomass w/ CCS Biomass w/o CCS Gas w/ CCS Gas w/o CCS Oil w/ CCS Oil w/o CCS Coal w/ CCS Coal w/o CCS TIMES_REF GCAM_BAU DEF IPAC_BAU DEF REMIND_BAU DEF WITCH_BAU DEF 21 TIMES_REF GCAM_BAU DEF IPAC_BAU DEF REMIND_BAU DEF 22 WITCH_BAU DEF TIMES_REF GCAM_BAU DEF IPAC_BAU DEF REMIND_BAU DEF 23 WITCH_BAU DEF TIMES_REF GCAM_BAU DEF IPAC_BAU DEF REMIND_BAU DEF WITCH_BAU DEF 24 TIMES_REF GCAM_BAU DEF IPAC_BAU DEF REMIND_BAU DEF WITCH_BAU DEF 25 The models use similar assumptions for the economic and population growth, and project that the carbon emissions will reach Gt CO2 by 25 in the reference scenario, about twice their level in 21. The differences in the various models are mainly attributed to: 1) slightly different regional definitions for China, 2) different base years and different data sources used for calibration, 3) different definitions of the reference scenario with different levels of policies and actions related to carbon mitigation in the reference.

21 Model comparisons for mitigation scenarios CO2 emission/mt 25 TIMES_C4555 TIMES_C3544 GCAM_45 DEF GCAM_55 DEF IPAC_45 DEF IPAC_55 DEF REMIND_45 DEF REMIND_55 DEF WITCH_45 DEF WITCH_55 DEF TIMES-C3544 TIMES-C4555 GCAM-55 DEF GCAM-45 DEF IPAC-55 DEF IPAC-45 DEF REMIND-55 DEF REMIND-45 DEF WITCH-55 DEF WITCH-45 DEF TIMES-C3544 TIMES-C4555 GCAM-55 DEF GCAM-45 DEF IPAC-55 DEF IPAC-45 DEF REMIND-55 DEF REMIND-45 DEF WITCH-55 DEF WITCH-45 DEF TIMES-C3544 TIMES-C4555 GCAM-55 DEF GCAM-45 DEF IPAC-55 DEF IPAC-45 DEF REMIND-55 DEF REMIND-45 DEF WITCH-55 DEF WITCH-45 DEF TIMES-C3544 TIMES-C4555 GCAM-55 DEF GCAM-45 DEF IPAC-55 DEF IPAC-45 DEF REMIND-55 DEF REMIND-45 DEF WITCH-55 DEF WITCH-45 DEF TIMES-C3544 TIMES-C4555 GCAM-55 DEF GCAM-45 DEF IPAC-55 DEF IPAC-45 DEF REMIND-55 DEF REMIND-45 DEF WITCH-55 DEF WITCH-45 DEF Primary energy consumption/ej Other Ocean Geothermal Solar Wind Nuclear Hydro Biomass w/ CCS Biomass w/o CCS Gas w/ CCS Gas w/o CCS Oil w/ CCS Oil w/o CCS Coal w/ CCS Coal w/o CCS TIMES_C4555 TIMES_C3544 GCAM_45 DEF GCAM_55 DEF IPAC_45 DEF IPAC_55 DEF REMIND_45 DEF REMIND_55 DEF WITCH_45 DEF WITCH_55 DEF All the models illustrate the importance of renewable energy sources excluding biomass (mainly hydro, wind and solar) for carbon mitigation, which will have continuously increasing shares in the primary energy consumption, reaching to 7%-15% in the 45 CO2eq stabilization scenario in the global models and 11% in the C4555 scenario in China TIMES by Carbon price (25 US$/tCO2)

22 Model comparisons for mitigation scenarios Despite the similarities, there are larger differences in the climate policy scenarios than in the reference scenario across models. The differences are mainly due to: different targets,; different model structures and modeling approaches; different model assumptions on technology availability and technoeconomic characteristics of the technologies (in particular, biomass power generation with CCS and biomass liquefaction with CCS; The sharp reductions of the energy demand together with large scale deployment of biomass liquefaction and power generation in combination with CCS (15%-3% in the primary energy consumption in 25 in GCAM and REMIND), make it possible to reduce carbon emissions in 25 below 5GtCO2.

23 Model comparisons for mitigation scenarios The sharp reductions of the energy demand (more than 8% reduction of the energy intensity per unit of GDP compared to the year 21 by 25), together with large scale deployment of biomass liquefaction and power generation in combination with CCS (15%-3% in the primary energy consumption in 25 in GCAM and REMIND) or large deployment of nuclear power, make it possible to phase out coal fast (less than 1% in the primary energy consumption in 25) to reduce carbon emissions in 25 below the level in 25 (around 5 GtCO2).

24 Summary With economic growth, China s energy consumption and carbon emissions are expected to increase steadily if without considerable mitigation efforts. Stringent carbon mitigation scenarios not only require substantive deployment of low- and non- carbon technologies but also significant change of both production mode and consumer behavior. However, whether it is realistic for the large scale development of nuclear, wind, solar and CCS technologies (in particular biomass with CCS) needs further investigation. The impact of sharp reductions in energy service demands on the GDP, industrialization, urbanization, living standards, employment and other social-economic aspects also need to be further investigated.

25 Thank you for your attention