Understanding CCS in China s Mitigation Strategy using GCAM-China

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1 Understanding CCS in China s Mitigation Strategy using GCAM-China SHA YU, JILL HORING, LEON CLARKE, PRALIT PATEL, JEFF MCLEOD, BO LIU, AND HAEWON MCJEON JOINT GLOBAL CHANGE RESEARCH INSTITUTE 1

2 GCAM-China Regional Modeling in a Global Context! To explore regional activities in China, we have added subnational detail to GCAM (version name: GCAM-China): Standard GCAM: 32 geopoli5cal regions! 31-province energy and economic system! Agriculture and land use by AEZ! Water supply and demand at major watershed scale! The rest of the model operates normally, thus providing global constraints and context. 2

3 Current GCAM-China Detail! Socioeconomics at the provincial level! Population! GDP! Energy transformation at the provincial level! Electricity generation and refining by province! Electricity trade within 6 grid regions! Renewable and carbon storage resources at the provincial level! Wind and solar! Carbon storage! Final energy demand at the provincial level! Buildings: commercial, urban residential, and rural residential! Transportation: passenger & freight with detailed technologies! Industry: aggregate energy demand! Not modeled at the provincial level! Fossil resources! Agricultural demand and supply! Water demand and supply! Air pollutant emissions 3

4 Provincial CCS Cost Curves! 1,600 large CO 2 point sources (power plants and industrial sources)! 2,300,000 MtCO 2 storage capacity! Deep saline sedimentary, EOR, coal basins! Significant opportunity for both lowcost and moderately priced storage Cost ($/tco 2 ) Inner Mongolia (Erlian Basin, Ordos Basin) Shandong (Bohai Bay Basin) Oil Fields Coal Regions Deep Saline Forma5ons ,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 Cumula5ve Supplied CCS Capacity (MtCO 2 /y) Sources: Dahowski et al., ,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 Cumula5ve Supplied CCS Capacity (MtCO 2 /y) 4

5 How do development pathways and provincial variations affect future energy use in China? Scenario development High Energy Future Low Provincial Varia(on Without With Consump(on Boom v Deepening social reform focusing on equality v Economic booms v ShiT towards western lifestyle Dispersed Growth v Widening regional disparity v More living space and energy services v Conflicts between economic development & environmental protec5on Sustainable Development v Rapid economic development v Growing middle class v Emphasis on sustainable growth & social equity Hub and Spoke v Substan5al growth in highincome and costal provinces v Strong technology innova5on and efficiency improvement v Environmental consciousness 5

6 What are the primary applications for CCS through 2050? 6

7 Consump(on Boom Scenario 2030 Emissions Sequestra(on Unit: Gt CO 2 Unit: Mt CO Unit: Gt CO 2 Unit: Mt CO Unit: Gt CO 2 Unit: Mt CO 2 7

8 Consump(on Boom Scenario Sequestra(on Emissions 2030 Capture is driven by emissions, energy structure, and available storage 2040 High emissions, high capture: Shandong

9 Consump(on Boom Scenario Sequestra(on Emissions 2030 Capture is driven by emissions, energy structure, and available storage 2040 Moderate emissions, high capture: Inner Mongolia

10 Consump(on Boom Scenario Sequestra(on Emissions 2030 Capture is driven by emissions, energy structure, and available storage 2040 High emissions, low capture: Guangdong

11 Top 10 provinces in CO 2 capture in 2030 show diverse profile; most captures are from the industrial sector Carbon Capture (MtCO 2 ) % of total capture from top 8 provinces Inner Mongolia Liaoning Hebei Shanxi Shandong Henan Sichuan Hubei Hunan Zhejiang Unit: Mt CO Synfuel produc(on Industry Electricity

12 Electricity sector responsible for most capture in top provinces by 2050 Carbon Capture (MtCO 2 ) % of total capture from top 7 provinces Inner Mongolia Hebei Shanxi Shandong Henan Jiangsu Sichuan Hubei Zhejiang Hunan Unit: Mt CO 2 0 Synfuel produc(on Industry Electricity 12

13 Will storage capacity be a constraint for future CCS deployment? 13

14 Provincial storage utilization by 2050 shows that CCS can be sustained % Storage Utilization 10% Storage Utilization Shandong Inner Mongolia Cumula(ve Capture (MtCO 2 ) No/Little On-shore Storage Capacity Xinjiang Gansu Beijing Ningxia Yunnan Qinghai Sichuan Jiangxi Hunan Shaanxi Hubei Chongqing Shanghai Tianjin Jilin Anhui Heilongjiang Guizhou Zhejiang Liaoning Henan Shanxi Jiangsu 0.00 Fujian Guangdong Guangxi Onshore Storage (MtCO 2 ) Tibet Hainan Hebei Top 10 provinces in cumula5ve CO 2 capture ( ) 14

15 Storage would become a more important constraint towards the end of the century % Storage Utilization Cumula(ve capture (MtCO 2 ) Hubei Zhejiang Hunan Shaanxi Sichuan Liaoning Jiangxi Chongqing Shanghai Tianjin Guizhou Anhui Jilin Heilongjiang Inner Mongolia Henan Shanxi Hebei Jiangsu Shandong Top 10 provinces in cumula5ve CO 2 capture ( ) Beijing Ningxia Xinjiang Gansu Yunnan Guangdong Qinghai Guangxi 0 Tibet Fujian Hainan Onshore Storage (MtCO 2 ) % Storage Utilization 15

16 Questions? 16