Development of Low-carbon Society Scenarios

in Bhutan 2050

Kei GomiNational Institute for Environmental Studies

Yuki OchiE-konzal, inc.

2018/Feb/08 NIES, Japan

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Contents

1. Concept, methodology and example of Low-carbon Society (LCS) Scenarios

2. Bhutan LCS scenario 2050

3. Exercise: Develop your own scenarios

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Concept, methodology and example of Low-carbon Society Scenarios

• Mitigation of climate change• GHG emissions

• Mitigation options

• Methodology for developing LCS scenarios

• Case studies in Malaysia and Indonesia

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Sources: World Resource Institute http://www.wri.org/

China, 11,601

United States, 6,319

India, 3,202

Indonesia, 2,472 Russian Federation,

2,030

Brazil, 1,357

Japan, 1,322

Canada, 867

Germany, 817

Iran, 801

Mexico, 729 Korea, Rep. (South), 632

Saudi Arabia, 583

South Africa, 527

Australia, 523

United Kingdom, 494

Nigeria, 492

Argentina, 443

Zambia, 380

Thailand, 374 ROW, 11,385

GHG Emissions in 2014 (MtCO₂e)

GHG emissions by country

4

5

Per Capita Emissions19.8

14.1

11.9

10.4 10.1 9.7 9.7

8.5 7.6

6.7 6.6 6.2 6.1

3.8 3.6 2.5

Per Capita GHG emissions in 2014 (tCO2eq)

Sources: World Resource Institute http://www.wri.org/

Emission and Temperature rise

• RCP2.6 (41～72%reductionin2050)“Likely”achievesthe 2 degree target

• RCP4.5(24～38%reductionin2050)“Moreunlikelythanlikely”

6Source: IPCC AR5, WG3, SPM, Table SPM.1

-50% by 2050

Source: IPCC AR5, WG3, SPM, Fig.SPM.4

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Strategy for Mitigation

• Evaluation of mitigation options• Alternative options

• “Marginalabatementcostcurve”

• Co-benefit / ancillary benefit

• Simulation of society as a whole• Integrated modeling

• Low-carbon society Scenarios

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Mitigation Options (Energy)• Energy efficiency improvement: Provide utility output with less

energy input

• Demand sectors: Residential, Commercial, Industrial, Transport

• Supply sectors: Power generation and transmission

• Fuel switch: Choosing fuel with less GHG emissions for unit energy output

• Natural gas, nuclear, renewable energies

• Energy service reduction/shifting: Reducing level of activities demanding energy input

• Compact city structure, modal shift

• Coolbiz, HEMS/BEMS

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Mitigation Options (Non-energy)

• Capturing GHG: Carbon capture and storage (CCS) • In powerplant and steal furnace

• Waste management: Reduce CH4 from landfill and CO2 from fossil carbon combustion• 3R (Reduce, Reuse and Recycle)• Energy recovery from incineration, CH4 collection from landfill

• Agriculture• Shifting feeds, appropriate fertilizer use, paddy field water

management, etc.

• Forestry, Land use and land-use change• Tree planting, reducing deforestation

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130+ options

Transport Business

LifestyleNew/Renewable

EnergyTown/

buildingsForest

conservation

How to choose?

12Source: Hibino (2010) Japan's Marginal Abatement Cost Curve Analysis and Mitigation Measures

“MarginalAbatementCost(MAC)”curve(Japan,2020)

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Cost per unit of GHG

reduction

Reduction potential

Wide & Low is better!

Efficient electric device in commercial sector

Insulated house

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Your cost is income of someone else.

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Source: IPCC AR5, WG3, SPM, Table SPM.4

What to consider?

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Potential CostCo-benefit(Ancillary benefit)

Certainty RiskSocial

acceptance

What to consider?

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Potential CostCo-benefit(Ancillary benefit)

Certainty RiskSocial

acceptance

Co-benefit

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Energy security

Transport convenience

Air pollution abatement

LandscapeSaving landfill

siteConserving resource

EmploymentAccess to

energyFuel poverty

What to consider?

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Potential CostCo-benefit(Ancillary benefit)

Certainty RiskSocial

acceptance

Social acceptance: Landscape

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“Low-carbon society scenarios”

• Scenario: future image, computer-aided stories

• Alternative future societies achieving climate goals

• Not“Prediction”!

• “Back-casting”

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Vision

Socio-economic indicators

Energy demand

GHG emissions

LC measures

Target year

Roadmap

Schedule of measures

Cost to implement measures

GHG emissions reductions

Ancillary benefit of measuresPresent

Scenario

Back-casting Approach

Basic of

GHG emission Projection

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Base year

Baseline

Policy

GH

G e

mis

sio

ns

Time

CO2 emissions from energy use

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CO2 emission =

Driving force

Energy service

demand

Driving force

Energy demand

Energy service

demand

x x x

CO2 emission

Energy demand

CO2 emissions from energy use

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CO2 emission =

Driving force

Energy service demand

Driving force

Energy demand

Energy service

demand

x x x

CO2 emission

Energy demand

Energy service :

Utility provided by using energy

Example:

Watching TV

Lighting a room

Cooling of spaces

Transporting one person by 10km

Producing iron & steel products

27

28

Energy service

intensity

Energy efficiency

CO2 intensity

Driving force

Energy service

demand

Driving force

Energy demand

Energy service

demand

x x x

CO2 emission

Energy demand

29

Driving force

x x x

Energy service

intensity

Energy efficiency

CO2 intensity

30

Driving force

x x x

Energy service

intensity

Energy efficiency

CO2 intensity

• Population and/or household• GDP by industry• Commercial floor area• Number of workers• Number of passenger trips by mode• Tons of freight transported

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Driving force

x x x

Energy service

intensity

Energy efficiency

CO2 intensity

• Air conditioner per household• Number of computers per office worker• Average travel distance of passengers• Average transport distance of freights• Iron production per GDP

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Driving force

x x x

Energy service

intensity

Energy efficiency

CO2 intensity

• Performance of air conditioner• Power use of computers• Fuel cost of vehicles• Coal input for per ton of iron production

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Driving force

x x x

Energy service

intensity

Energy efficiency

CO2 intensity

• Share of fuels for cooking• Share of fuels for vehicles• Share of energy sources for power generation• Efficiency of coal/gas fired-powerplant

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Driving force x x xEnergy service

intensityEnergy efficiency CO2 intensity

ResidentialUrban householdRural household

CommercialWholesale & RetailRestaurant & HotelProfessional servicesPublic services

IndustriesPrimary industriesManufacturingConstruction

TransportPassengerFreight

Residential & CommercialAir conditioning, CookingWater heating, LightingOthers

IndustriesIndustrial boiler, Industrial motorFurnace, Others

TransportPassenger cars, Bus, TrainMotorbike, Freight cars

Demand sideElectricityNatural gasGasoline, CoalBiomass

Supply sideOil, Coal, Natural gasHydro energyNuclear energyPhotovoltaicWind power

In Baseline & Policy Scenarios

Simulation by “Integrated Modelling”

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Export by goods

Government expenditure

Investment

Import rate

Input coefficient matrix

Household size

Floor area per outputFreight generation per

output

Transport distance

Modal share

Trip per person

Trip distance

Modal share

Energy service demand per driving force

Fuel share

Energy efficiency

CO2 emission factor

IO analysis

Output by industry

Population

Number of household

Output of commercial industry

Commercial building floor

area

Freight transport demand

Passenger transport demand

Population

Energy service demand

Output of manufacturing

industry

Exogenous variablesParameters

Endogenous variables

Final energy demand

Energy demand (DPG)

Central power generation (CPG)

Energy demand (CPG)

Primary energy supply

Dispersed power generation (DPG)

CO2 emssions

Energy efficiency DPG

Energy efficiency (CPG)

Fuel share (CPG)

Transmission loss (CPG)

Own use (CPG)

Energy end-use device share

Energy end-use device energy efficiency

Carbon sink

Private consumption

Integration of all emission sectors

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Forestry

Energy

• Crop production• Livestock

population• Biofuel production

• Wood production• Degraded and

deforested area

• Biofuel

• Population• Production• Transport

• Food & feed demand

• Population

• Population• Production

• Agri-waste

• Waste to energy

• Wood demand

Economy and demography

Waste management

• Fuel wood demand

Biofuel

• Residue

• Fuel crop Land-use

Agriculture

LCS scenario with Integrated ModelingA case in Malaysia

2005 2020 20302020/2005

2030/2005

Population 26.1 32.8 37.3 1.3 1.4 Million

Household 5.8 8.2 9.3 1.4 1.6 Million

GDP 509 996 1,601 2.0 3.1 Bill. RM

Per capita GDP 19.5 30.4 43.0 1.6 2.2 1000.RM

Gross output 1,604 3,135 4,929 2.0 3.1 Bill. RM

Primary 55 84 97 1.5 1.8

Secondary 920 1,507 2,175 1.6 2.4

Tertiary 629 1,544 2,657 2.5 4.2

Passenger transport

169 315 359 1.9 2.1 Bill. pass-km

Freight transport

92 150 214 1.6 2.3 Bill. t-km

Projected output by 26 sectors

380

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

2005 2020 2030

Bill

. R

M

Public ServicesOther Private ServicesEducation, Research & DevelopmentAccomodation & RestrauntsWholesale & RetailReal EstateFinance & InsuranceTransport ServicesWater WorksElectricity & Gas supplyConstructionOther Manufacturing ProductsTransport EquipmentsElectric and Electronic EquipmentsGeneral MachineryOther Metal ProductsIron & SteelCement, Ceramic, Stone & Cray ProductsChemical ProductsPetrolium Refinery & Coal ProductsPaper & PulpTextiles & Wearing ApparelFood, Drink & Tabacco ProductsOther MiningOil and Gas MiningAgriculture, Forestry & Fishing

Tertiary industries

Secondary industries

Primary industries

Projected transport volume

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Freight transportPassenger transport

0

50

100

150

200

250

300

350

400

2005 2020BaU

2030BaU

Bill

. pas

s-km

Bicycle

Walk

Two wheelers

Train

Bus

Vehicles

0

50

100

150

200

2005 2020 2030

Bill

. t-k

m

Train

Vehicle

LCS scenario with Integrated ModelingA case in Malaysia

40 Periods between projected years were interpolated linearly.

BaU CM1 CM22000

2005

2010

2015

2020

2025

2030

0

100

200

300

400

500

600

700

800

2000

2005

2010

2015

2020

2025

2030

MtC

O2eq

2000

2005

2010

2015

2020

2025

2030

Others

LULUCF

Agriculture

Waste

Fgt. Transport

Pass. Transport

Industry

Commercial

Residential

• GHG emissions

0.62

0.52 0.53

0.41

0.31

0.43

0.21 0.21

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

2000(NC2)

2005 2020BaU

2020CM1

2020CM2

2030Bau

2030CM1

2030CM2

kgC

O2eq

/RM

Emission intensity (GHG emission per GDP)

41

-22% from 2005

-40% from 2005

Per capita GHG emission

42

9.4 10.2

16.1

12.4

9.5

19.5

9.5 9.5

0

3

6

9

12

15

18

21

2000(NC2)

2005 2020BaU

2020CM1

2020CM2

2030Bau

2030CM1

2030CM2

tCO

2eq

Contribution to emission reduction in 2020

43

CM1 CM2

EEI in demand sectors

38%

EEI in power supply

11%

Renewable energy

8%

Modal shift4%

Waste18%

Agriculture1%

Forestry&Landuse

18%

Others2%

EEI in demand sectors

32%

EEI in power supply

14%Renewable

energy11%

Modal shift5%

Waste7%

Agriculture1%

Forestry&Landuse

29%

Others1%

Indonesia ScenariosGHG emissions

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0.3

1.0 1.0 0.9 0.9

3.5

2.4 2.1 2.1

1.6

1.7

1.0 1.2 1.0

1.7

0.9 1.1 1.0

0

1

2

3

4

5

6

BaU CM1 CM2 CM3 BaU CM1 CM2 CM3

2005 2020 2050

GtC

O2eq

エネルギー

AFOLU

1.9

2.7

2.0 2.0 1.9

5.3

3.3 3.2 3.1

Energy

BaU: Business as usualCM1: Current policyCM2: Current policy + BiofuelCM3: CM2 + utilizing abandoned land

Biofuel had adverse impact

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2,006 2,047

1,907

1600

1700

1800

1900

2000

2100

2200

CM1 CM2 CM3

MtC

O2eq

GHG emission in 2020

+42MtCO2eq bybiofuel

Deforestation for biofuel production increase total GHG emissions

46

(73) (73)

97

(66)

18

41 41

(99)-100

-50

0

50

100

CM2 CM3

MtC

O2

eq

Decomposition of emission change from CM1

エネルギー

土地利用転換

泥炭火災・酸化

合計

Energy

Land-use change

Peat fire

Total

Summary

• LCS scenario can support policy making for long-term mitigation goals

• Appropriate mitigation options should be chosen considering cost, effectiveness, co-benefit and risk

• Modeling can compare different options by quantifying there potentials

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