Larissa P. N. de Oliveira
VITO/EnergyVille
“Climate policy Engagement in Brazil: how
delayed action might lead to CCS as t...
Contents
1.Research Background
2.Introduction
3.Methodology
4.Results
5.Conclusions
6.Future Work
Background
• Original Work
– Oliveira, L. P. N. “Temporal Issues in Mitigation Alternatives for the
Energy Sector in Brazi...
Introduction
• Motivation
– Different approaches regarding time preference lead to different
outcomes in scenario-making;
...
Brazil’s Context
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Brazil World
Energy Supply - 2012
Non-renewable Renewable
Brazil’s Context
Hydraulic
11%
Firewood and
charcoal
8%Sugarcane
products
16%
Other renewables
4%
Petroleum and oil
produc...
Brazil’s Context
0
500000
1000000
1500000
2000000
2500000
1990 1995 2000 2005 2010
GgCO2
CO2 Emissions
Energy Industrial P...
Brazil’s in a crossroads…
• On the demand side:
– Increasing population
– Economic growth in recent years
– Increasing dem...
Brazil’s Context
• Low Carbon Policies
Before...
 PNMC: 36.1% to 38.9%
reduction in 2020
compared to a BAU
scenario (volu...
Methodology
• Integrated Modeling Tool : TIMES
• TIMBRA
– Intertemporal optimization – perfect foresight
• 5 energy levels...
Methodology
• Simplified structure
Methodology
• Simplified structure: resources
Methodology
• Simplified Structure: Liquid fuels and H2
Methodology
• Simplified structure: Electricity Generation
Methodology
• Simplified structure: Transport Sector
Methodology
• Simplified structure: other demand sectors
Industry:
Mining
Cement
Ceramics
Pulp and Paper
Pig-iron and Stee...
Methodology
• Simplified Structure
Methodology
• Scenarios:
– Discount rates:
• Market discount rates
per sector: 12%-15%
• Social discount rate: 3%
BASE_MKT...
Main Results
0
200
400
600
800
1,000
1,200
1,400
BASE_MKTS
LC_MKTS_PF
LC_MKTS_PFD
BASE_MKTS
LC_MKTS_PF
LC_MKTS_PFD
BASE_MK...
Main Results
• Primary sources across scenarios:
0
1
2
3
4
5
6
7
Coal
Natural Gas
Crude oil
Biomass
Biofuels
Nuclear
Hydro...
Main Results
• Primary sources across scenarios:
0
1
2
3
4
5
6
7
Coal
Natural Gas
Crude oil
Biomass
Biofuels
Nuclear
Hydro...
Main Results
• Abated
emissions
through CCS
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
Capture
EE
Capture
Bio
Capture
H2
BAS...
Main Results
• Normalized Global Cost vs. Normalized
Emissions of Scenarios.
1.002
1.004
1.006
1.008
1.010
1.012
1.014
1.0...
Conclusions
• Energy budget of Brazil’s INDC seems to be quite stringent
under high long-term economic growth premises;
• ...
Future work for TIMBRA
• Better depiction of demand side processes  should relief
the pressure for CCS and other advanced...
Thank you!
Larissa P. N. de Oliveira
larissa.oliveira@energyville.be
Co-authors:
Roberto Schaeffer, Ph.D
roberto@ppe.ufrj....
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Climate policy Engagement in Brazil: how delayed action might lead to CCS as the last resort to mitigation

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Climate policy Engagement in Brazil: how delayed action might lead to CCS as the last resort to mitigation

  1. 1. Larissa P. N. de Oliveira VITO/EnergyVille “Climate policy Engagement in Brazil: how delayed action might lead to CCS as the last resort to mitigation” ETSAP Workshop – 27/11/2016 Madrid
  2. 2. Contents 1.Research Background 2.Introduction 3.Methodology 4.Results 5.Conclusions 6.Future Work
  3. 3. Background • Original Work – Oliveira, L. P. N. “Temporal Issues in Mitigation Alternatives for the Energy Sector in Brazil”, D.Sc. Thesis. Energy Planning Program, Federal University of Rio de Janeiro (2016). • “Sandwich” period (1 year) at Imperial College London – Overall subject: Integrated modelling for evaluating low carbon policies in Brazil • Other publications: – OLIVEIRA, L. P. N.; ROCHEDO, P. R. R., PORTUGAL-PEREIRA, J.; HOFFMANN, B. S.; ARAGÃO, R.; MILANI, R.; LUCENA, A. F. P.; SZKLO, A. S.; SCHAEFFER, R. Critical technologies for sustainable energy development in Brazil: technological foresight based on scenario modelling. Journal of Cleaner Production 130 PP. 12-24. – LUCENA, A. F. P.; CLARCKE, L.; SCHAEFFER, R.; SZKLO, A. S.; ROCHEDO, P. R. R.; NOGUEIRA, L. P. P.; DAENZER, K.; GURGEL, A.; KITOUS, A., KOBER, T. Climate policy scenarios in Brazil: A multi-model comparison for energy. Energy Economics 56 PP. 564-574, 2016. – NOGUEIRA, L. P. P.; LUCENA, A. F. P.; RATHMANN, R.; ROCHEDO, P. R. R.; SZKLO, A. S.; SCHAEFFER, R. Will thermal power plants with CCS play a role in Brazil's future electric power generation? International Journal of Greenhouse Gas Control 24 PP. 115-123, 2014. – NOGUEIRA, L. P. P.; HAWKES, A. D.; NAPP, T. Can Brazil fulfil long-term reduction targets? An Evaluation of Consequences of Delayed Action on its energy sector. 9th Conference on Sustainable Development of Energy, Water and Environmental Systems (SDEWES). Venice-Istanbul, September, 2014.
  4. 4. Introduction • Motivation – Different approaches regarding time preference lead to different outcomes in scenario-making; – Brazil has assumed a strong position towards climate change, but faces an economic and political turmoil; – Bring the debate of delayed action to country level; – Bring insight on the effect of delayed action in Brazil (considering its particularities). • Research question: – Could Brazil become locked on fossil fuel technologies if it does not anticipate climate action? Integrated Modeling Time preference Climate Change
  5. 5. Brazil’s Context 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Brazil World Energy Supply - 2012 Non-renewable Renewable
  6. 6. Brazil’s Context Hydraulic 11% Firewood and charcoal 8%Sugarcane products 16% Other renewables 4% Petroleum and oil products 39% Natural gas 14% Coal and coke 6% Uranium 1% Other non- renewables 1%
  7. 7. Brazil’s Context 0 500000 1000000 1500000 2000000 2500000 1990 1995 2000 2005 2010 GgCO2 CO2 Emissions Energy Industrial Processes Land Use Change and Forestry Waste Treatment
  8. 8. Brazil’s in a crossroads… • On the demand side: – Increasing population – Economic growth in recent years – Increasing demand in the long-term • Despite current economical crisis • On the supply side: – Still highly renewable (due to hydro and ethanol) – Hydro reminiscent potential in Amazon region – Pre-salt discoveries  increased natural gas consumption – Low cost coal-fired electricity generation
  9. 9. Brazil’s Context • Low Carbon Policies Before...  PNMC: 36.1% to 38.9% reduction in 2020 compared to a BAU scenario (voluntary). Today:  INDC: absolute targets of 1.3 GtCO2e until 2025 and 1.2 GtCO2e until 2030 (37% and 43% reduction) in relation to 2005 levels.
  10. 10. Methodology • Integrated Modeling Tool : TIMES • TIMBRA – Intertemporal optimization – perfect foresight • 5 energy levels (+2 dummies): – Resources: 4 types (non-renewables) – Primary Energy: 8 types – Secondary Energy: 18 types – Final Energy: 20 types – Useful Energy: supplies 22 demand types – Around 300 technology types – Base year: 2010 – Time Horizon: 2010-2050, 5-year periods.
  11. 11. Methodology • Simplified structure
  12. 12. Methodology • Simplified structure: resources
  13. 13. Methodology • Simplified Structure: Liquid fuels and H2
  14. 14. Methodology • Simplified structure: Electricity Generation
  15. 15. Methodology • Simplified structure: Transport Sector
  16. 16. Methodology • Simplified structure: other demand sectors Industry: Mining Cement Ceramics Pulp and Paper Pig-iron and Steel Nickel & Iron Iron-alloys Chemical Food and Bev. Textile Others
  17. 17. Methodology • Simplified Structure
  18. 18. Methodology • Scenarios: – Discount rates: • Market discount rates per sector: 12%-15% • Social discount rate: 3% BASE_MKTS LC_MKTS_PF LC_MKTS_PFD BASE_SOC LC_SOC_PF LC_SOC_PFD – Low carbon policies: • Based on INDC for 2030 - 575,8 million tCO2 • Early (2030) vs. delayed action (2040) reflects level of international cooperation.
  19. 19. Main Results 0 200 400 600 800 1,000 1,200 1,400 BASE_MKTS LC_MKTS_PF LC_MKTS_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD 2010 2020 2030 2040 2050 TWh Electricity Generation Ethanol H2 CCGT MSW Wave Solar Hybrid Solar Wind Biomass w/CCS Biomass Hydro Nuclear Diesel Fuel Oil NG w/CCS NG Coal Co-firing Coal w/CCS Coal 0 200 400 600 800 1,000 1,200 1,400 BASE_MKTS LC_MKTS_PF LC_MKTS_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD 2010 2020 2030 2040 2050 MtCO2 CO2 Emissions CO2 Capture - H2 CO2 Capture - Bio CO2 Capture - EE Net Emissions 0 200 400 600 800 1,000 1,200 1,400 BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_SOC LC_SOC_PF LC_SOC_PFD 2010 2020 2030 2040 2050 TWh Electricity Generation Ethanol H2 CCGT MSW Wave Solar Hybrid Solar Wind Biomass w/CCS Biomass Hydro Nuclear Diesel Fuel Oil NG w/CCS NG Coal Co-firing Coal w/CCS Coal 0 200 400 600 800 1,000 1,200 1,400 BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_SOC LC_SOC_PF LC_SOC_PFD 2010 2020 2030 2040 2050 MtCO2 CO2 Emissions CO2 Capture - H2 CO2 Capture - Bio CO2 Capture - EE Net Emissions More fossil- based More renewables Market DR Social DR
  20. 20. Main Results • Primary sources across scenarios: 0 1 2 3 4 5 6 7 Coal Natural Gas Crude oil Biomass Biofuels Nuclear Hydro Other Renewables 2030 BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD
  21. 21. Main Results • Primary sources across scenarios: 0 1 2 3 4 5 6 7 Coal Natural Gas Crude oil Biomass Biofuels Nuclear Hydro Other Renewables 2050 BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD
  22. 22. Main Results • Abated emissions through CCS 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 Capture EE Capture Bio Capture H2 BASE_SOC LC_SOC_PF LC_SOC_PFD BASE_MKTS LC_MKTS_PF LC_MKTS_PFD
  23. 23. Main Results • Normalized Global Cost vs. Normalized Emissions of Scenarios. 1.002 1.004 1.006 1.008 1.010 1.012 1.014 1.016 1.018 0.68 0.70 0.72 0.74 0.76 0.78 NormalizedTotalCost Normalized Emissions LC_SOC_PFD LC_SOC_PF LC_MKTS_PFD LC_MKTS_PF delayed early early delayed
  24. 24. Conclusions • Energy budget of Brazil’s INDC seems to be quite stringent under high long-term economic growth premises; • Different elements related to time preference influence the technology transition: among them the discount rate choice and the level of international cooperation; • Still, under delayed action, Brazil’s energy system gets (more) locked in fossil technologies  bioCCS potential, e.g., is underexplored. • Perfect foresight results deviate from real market rationale of some specific sector (e.g., ethanol + EE). • Important to be aware of discounting effects and model rationale when interpreting results (expl: early vs. delayed actions with different DRs).
  25. 25. Future work for TIMBRA • Better depiction of demand side processes  should relief the pressure for CCS and other advanced technologies; • Better depiction of industry sector; • Adjustments in short-term macroeconomic assumptions to reflect current economical crisis; • Sensitivities related to discount rates; • Allowing trade with other regions  ‘cap-and-trade’ shouuld also relief pressure on supply; • Integration with Latin America (ongoing).
  26. 26. Thank you! Larissa P. N. de Oliveira larissa.oliveira@energyville.be Co-authors: Roberto Schaeffer, Ph.D roberto@ppe.ufrj.be Alexandre Szklo, D.Sc. szklo@ppe.ufrj.br Adam D. Hawkes, Ph.D. a.hawkes@imperial.ac.uk This research was financed by CNPq and CAPES, funding agencies in Brazil. This research was partly financed by ‘Science Without Borders’ Program (http://www.cienciasemfronteiras.gov.br/web/csf-eng/).

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