adaptação às mudanças climáticas no brasil: cenários e ... · equipe: bruno borba, pedro...

Adaptação às mudanças climáticas no Brasil: cenários e alternativas

Coordenação: Roberto Schaeffer, André Lucena, Alexandre Szklo, Rafael Kelman

Equipe: Bruno Borba, Pedro Rochedo, Larissa Nogueira , Alexandre Koberle, Pedro Avila, Tainá Cunha e Bernardo Bezerra

2015


▪ Introdução

▪ Ferramentas e Premissas

▪ Metodologia

▪ Resultados


Introdução

Introdução

▪ Projeto contratado pela Secretaria de Assuntos Estratégicos da Presidência da República (SAE-‐PR) em 2015 ▪ Colaboração COPPE-‐PSR

▪ Objetivos: ▪ Quais são os impactos das mudanças climáticas no Sistema interligado

brasileiro? ▪ Quais seriam as melhoras alternativas para compensar a redução de

geração hidroelétrica? ▪ Melhor estratégia de adaptação: operação vs expansão?

▪ Como políticas de mitigação podem afetar estas alternativas?

http://www.ons.org.br/

Sistema Interligado Nacional (SIN)

Sazonalidade hidrológica no Brasil(Séria histórica 1931 – 2009)

Source: Silva (2012)


Ferramentas e Premissas

MESSAGE-Brasil 300

▪ Modelo de otimização intertemporal (perfect foresight) ▪ 5 níveis energéticos (+2 intermediários):

▪ Recursos: 4 (não renováveis) ▪ Energia Primária: 8 ▪ Energia Secundária: 18 ▪ Energia Final: 20 ▪ Energia Útil/Serviço Energético: 22 demandas

▪ Cerca de 300 tecnologias de conversão ▪ Ano base: 2010 ▪ Horizonte: 2010-‐2050 em períodos de 5 anos

Model for Energy Supply Systems and their General Environmental Impacts

SDDP

▪ SDDP é um modelo de despacho hidrotérmico estocástico; ▪ Representação da rede de transmissão para estudos de

operação de longo, médio e curto prazo; ▪ Calcula a política operativa de mínimo custo de um sistema

hidrotérmico; ▪ Utilizado em estudos de planejamento operativo em mais de

30 países, incluindo: ▪ Todos os países das Américas Central e do Sul; EUA e Canadá; Áustria,

Espanha, Noruega Balcãs (10 países) e Turquia; Nova Zelândia, China e Shangai.

Premissas

▪ Cenário Macroeconômico: EPE (2014)

Premissas

▪ População: IBGE (2013)

Premissas

▪ General Circulation Models – GCM ▪ MIROC5 (menor impacto) ▪ HadGEM2-‐ES (maior impacto)

▪ Downscaling pelo modelo ETA (Chou et al., 2014)

▪ Modelos climáticos globais foram usados para gerar cenários hidrológicos para as bacias hidrográficas brasileiras ▪ Grupo de recursos hídricos do projeto (FUNCENE-‐UNB)

Premissas

▪ Cenários Climáticos -‐ Representative Climate Pathways (RCP) ▪ RCP 8.5: Assume nenhum esforço adicional para reduzir as emissões de

GEE do setor energético nacional ▪ RCP 4.5: Esforços nacionais para mitigar emissões de GEE ▪ Emissões brasileiras podem ter pouco peso nas emissões globais

Cenário Preço de Carbono 2020 2030 2040RCP 4.5 (2005)$/tCO2e 50 74 110

ETP, 2015


Metodologia

Procedimento MetodológicoModelagem Climática e Hidrológica

Projected Riverflow

Scenario Premisses (RCP 4.5 and 8.5)

Operation Model SDDP (PSR)

Expansion Model MESSAGE-‐Brazil

(COPPE)

Operation/ Expansion

Operation Impacts/ adaptation

Adaptation through expansion

Operation

GCM – Dow

scaling – Hy

drology Mod

el

195 riv

erflo

w se

ries

•Hydro generation scenarios •Marginal cost of operation •Deficit probability

•Capacity expansion •Investment costs •Second order effects

Procedimento MetodológicoModelagem Energética


Resultados

Somente resultados do HadGEM, com maior impacto hidrológico, serão apresentados.




(COPPE)




Operation

GCM – Dow

scaling – Hy

drology Mod

el

195 riv

erflo

w se

ries



Procedimento Metodológico




(COPPE)




Operation

GCM – Dow

scaling – Hy

drology Mod

el

195 riv

erflo

w se

ries



Procedimento MetodológicoLinha de Base

Baseline Scenarios

▪ Baseline scenarios: RCP comparison – Electricity

GW year

0.0

35.0

70.0

105.0

140.0

2010 2015 2020 2025 2030 2035 2040

Hydro Coal Gas OilNuclear Biomass Wind Solar

RCP 8.5 •BAU expansion – no explicit mitigation assumed

RCP 4.5 •Energy efficiency •Lower fossil expansion •100$/tCO2 Carbon cost (ETP, 2015)

Baseline Scenarios

▪ Baseline scenarios: RCP comparison – GHG Emissions




(COPPE)




Operation

GCM – Dow

scaling – Hy

drology Mod

el

195 riv

erflo

w se

ries



Procedimento MetodológicoAdaptação/Impacto da Operação

Results - Operation

▪ Hydropower Generation

Gwyear

0

23

45

68

90

2010 2015 2020 2025 2030 2035 2040

Base 8.5 HadGEM 8.5 Base 4.5HadGEM 4.5

Results Operation

▪ Risk of Shortage – HadGEM 8.5

Results Operation

▪ Accumulated Operation Cost – HadGEM 8.5




(COPPE)




Operation

GCM – Dow

scaling – Hy

drology Mod

el

195 riv

erflo

w se

ries



Procedimento MetodológicoAdaptação/Impacto da Expansão

Results – Adaptation

▪ HadGEM – RCP 8.5

GW year

0.0

35.0

70.0

105.0

140.0

2010 2015 2020 2025 2030 2035 2040


Lower hydro generation led to: •Increased coal •Increased wind (marginal)

Results – Adaptation

▪ HadGEM – RCP 4.5

GW year

0.0

40.0

80.0

120.0

160.0

2010 2015 2020 2025 2030 2035 2040


Lower hydro generation led to: •Increased wind •Increased gas •Increased coal (marginal)

Comentários Finais

▪ Detailed dispatch modeling requires detailed hydrological modeling ▪ Operational impacts can be severe and costly if there is no

adaptation ▪ Mitigation policies do impact optimal adaptation strategies.

▪ Electricity generation in Brazil can become more carbon intensive in a BaU scenario

▪ Adapting to a reduced hydropower availability may further increase Brazil’s emissions if no other actions are taken

▪ Adaptation can be achieved by combination of energy efficiency, renewable energy, etc.

▪ Impacts on other renewable sources?

Obrigado

Cenários mais recentes para o Brasil

Roberto Schaeffer

Center for Energy and Environmental Economics CENERGIA

since 2003

Our team at CENERGIA: ▪ Professors

– Alexandre Szklo – André F P Lucena – Roberto Schaeffer

▪ Researchers – Ten MSc students – Ten DSc students – Three Postdocs one third of our researchers are from abroad

Global IAMsModel Institute Region/Country Classification Algorithm

MESSAGE-‐GLOBIOM IIASA Austria General equilibrium Intertemporal optimization

REMIND-‐MAgPIE PIK Germany General equilibrium Intertemporal optimization

IMAGE/TIMER PBL Netherlands Partial equilibrium Recursive dynamic

GCAM PNNL USA General equilibrium Recursive dynamicAIM/CGE NIES Japan General equilibrium Recursive dynamic

WITCH-‐GLOBIOM FEEM Italy General equilibrium Intertemporal optimization

IGMS-‐EPPA MIT USA General equilibrium Recursive dynamicGEM-‐E3 EU-‐JRC-‐IPTS, ICCS European Union General equilibrium Recursive dynamicIMACLIM SMASH-‐CIRED France General equilibrium Recursive dynamicMERGE EPRI USA General equilibrium Intertemporal optimization

WorldScan CPB Netherlands General equilibrium Recursive dynamicTIAM-‐WORLD ETSAP France Partial equilibrium Intertemporal optimization

POLESCNRS-‐LEPII, Enerdata,

EU-‐JRC-‐IPTS France Partial equilibrium Recursive dynamic

COFFEE/TEA COPPE Brazil General equilibrium Intertemporal optimization

Below Equator line

Model Linkages/Iterations

TEA model is a computational general equilibrium (CGE) model under development, headed by Angelo Gurgel (EESP-‐FGV).

▪ Reference: GTAPinGAMS ▪ Features:

▪ Recursive dynamic: evolution of the global economy until 2100 ▪ Multi-‐regional: the same 18 COFFEE model’s regions ▪ Multi-‐sectorial: agriculture, energy, industry, transport and services represented in 16 sectors

▪ Productive factors: labor, capital, land and resources ▪ Full set of bilateral trades: transport costs, export taxes and tariffs ▪ Detailed energy sector representation: current and backstop techs

The TEA ModelTotal-‐Economy Assessment

The COFFEE Model

COmputable Framework For Energy and the Environment

▪ Optimization in partial equilibrium Bottom-‐up model

▪ Includes Energy System and Land System Completely integrated under one framework

▪ Representation of the land use system: Forest, pastures, cropland, flooded

▪ Emissions Sources: Fossil-‐fuel combustion from all sectors, industrial

processes, waste treatment, fugitive emissions and land-‐related

▪ 18 regions

The COFFEE Model

The COFFEE Model Energy System

The COFFEE Model Land System

The COFFEE Model Scenario Protocol

▪ Current Policies (NPi): based on currently implemented national policies

▪ NPi_1000: NPi + global budget of 1,000 GtCO2 (2°C scenario)

▪ NPi_1000_NoCCS: NPi + global budget of 1,000 GtCO2 (2°C scenario) + Unavailability of CCS (fossil and/or bioenergy)

COFFEE: Current PoliciesGlobal GHG Emissions

Cumulative Emissions: 3,885 GtCO2

COFFEE: Current PoliciesGlobal Primary Energy

COFFEE: Current PoliciesGlobal Land Change (Cumulative)

COFFEE: NPi_1000 (2ºC)Global GHG Emissions

COFFEE: NPi_1000 (2ºC)Global Primary Energy

COFFEE: NPi_1000 (2ºC)Global Carbon Capture and Storage

COFFEE: NPi_1000 (2ºC)Global Land Change (Cumulative)

COFFEE: NPi_1000 (2ºC) without CCSGlobal GHG Emissions

COFFEE: NPi_1000 (2ºC) without CCSGlobal Primary Energy

COFFEE: NPi_1000 (2ºC) without CCSGlobal Land Change (Cumulative)

COFFEE: Scenario ComparisonGlobal CO2 Emissions

Brazil Land-‐Use and Energy Systems Model ▪ Partial equilibrium – the full energy and land-‐use systems ▪ Emissions include fossil-‐fuel combustion from all sectors, industrial

processes, waste treatment, and fugitive emissions

▪ Includes a representation of the land-‐use system: ▪ Forests, savannas, low-‐ and high-‐capacity pastures, integrated systems, cropland,

double cropping, planted forests, protected areas

The BLUES model

Forest Low Cap Pasture

High Cap Pasture

Integrated Systems

Cropland Double Cropping

Planted Forest

Savanna

Recovered Pastures

Managed Forests

The BLUES modelLand Use transitions matrix

▪ Current Policies

▪ INDC forever

▪ INDC – 1,000 GtCO2 (2o C)

Few and fresh results from (but not out of the) Blues…

BLUES: Current Policies ScenarioGHG Emissions

Prim

ary En

ergy (M

toe)

0

125

250

375

500

2010 2015 2020 2025 2030 2035 2040 2045 2050

Oil Gas Coal Biomass Sugarcane Hydro Solar Wind Nuclear

BLUES: Current Policies ScenarioPrimary Energy Consumption

BLUES: INDC ScenarioGHG Emissions

Prim

ary En

ergy (M

toe)

0

125

250

375

500

2010 2015 2020 2025 2030 2035 2040 2045 2050


BLUES: INDC ScenarioPrimary Energy Consumption

Results - INDC Scenario

GWa Forest Cropland dbl_Crop Planted Forest

Lo Cap Pasture

Hi Cap Pasture

IntegratedSystem

Savanna

2010 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.02030 -‐12.9 14.0 5.2 3.0 -‐31.5 30.9 4.0 -‐12.42050 -‐12.9 17.1 9.3 4.3 -‐46.5 37.3 4.0 -‐12.4

By 2030:

• 31.5 Mha reduction in total Lo Cap pastures • 30.9 Mha increase in Hi Cap pastures • 3.0 Mha increase in planted forests • 4.0 Mha integrated systems • 9.3 Mha increase in double Cropping area

• Zero net deforestation post-‐2030 • Less forest loss; more savanna loss than NPi

• Exceeds INDC pasture recuperation target of 15 Mha • Meets 3.0 Mha target for planted forest increase • Meets 4.0 Mha target for integrated systems

Area (Mha)

Area (M

ha)

-‐90

-‐43

5

53

100

2010 2015 2020 2025 2030 2035 2040 2045 2050Forest Forest_PA Forest_Mg Croplanddbl_Crop Forest_Pl Low Cap Pasture High Cap PastureIntegratedSystem Recovered_Pasture Savanna Savanna_PA

BLUES: INDC_1000 Scenario (2ºC)GHG Emissions

Prim

ary En

ergy (M

toe)

0

125

250

375

500

2010 2015 2020 2025 2030 2035 2040 2045 2050


BLUES: INDC_1000 Scenario (2ºC)Primary Energy Consumption

Power Generaaon

TWh

0.0

350.0

700.0

1050.0

1400.0

2010 2020 2030 2040 2050

Hydro Imp. Coal Nat. Coal Gas OilBio Bagasse Nuclear Wind DGPV CHP

BLUES: Scenario Comparison

Power Generaaon Emissions – GHG Emission

MtCO2eq

0.0

17.5

35.0

52.5

70.0

2010 2015 2020 2025 2030 2035 2040 2045 2050

Npi -‐ Emissions INDC -‐ EmissionsINDC_MB -‐ Emissions


Biofuel Use

PJ

0.0

750.0

1500.0

2250.0

3000.0

2010 2020 2030 2040 2050Ethanol_1stGen Ethanol_2ndGen Biodiesel Biocoal Ethanol_BioCCS AdvBioKerosene_Oil_HEFA AdvBioKerosene_Bio_BTL AdvBioDiesel_BTLAdvBioDiesel_BTL_CCS


Transport Emissions

MtCO2eq

0.0

65.0

130.0

195.0

260.0

2010 2015 2020 2025 2030 2035 2040 2045 2050

Current Policies INDC INDC_1000

BLUES: Scenario ComparisonTransport Sector – GHG Emissions

Passenger Transport -‐ Energy use

PJ

0

750

1500

2250

3000

2010 2015 2020 2025 2030 2035 2040 2045

Gasoline Diesel Gas Biodiesel Ethanol_final Kerosene Bunker Elect

BLUES: Scenario Comparison (INDC_1000)Transport Sector – Passenger Energy Use

Obrigado

adaptação às mudanças climáticas no brasil: cenários e ... · equipe: bruno borba, pedro...

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