Development ofLow-carbon Society Scenarios
in Bhutan 2050
Kei Gomi
National Institute for Environmental Studies

Yuki Ochi
E-konzal, inc.
2018/Feb/08 NIES, Japan
1

Contents
1. Concept, methodology and example ofLow-carbon Society (LCS) Scenarios
2. Bhutan LCS scenario 2050
3. Exercise: Develop your own scenarios

2Concept, methodology and exampleof Low-carbon Society Scenarios• Mitigation of climate change• GHG emissions• Mitigation options• Methodology for developing LCS scenarios• Case studies in Malaysia and Indonesia

3

GHG emissions by country
GHG Emissions in 2014 (MtCO₂e‍)China, 11,601

Thailand, 374

ROW, 11,385

Zambia, 380
Argentina, 443

UnitedNigeria, 492
Kingdom, 494

Australia, 523
South Africa, 527
Saudi Arabia, 583
Korea, Rep.
Mexico, 729(South), 632
Iran, 801

United States, 6,319

India,
3,202

Canada, 867
Germany, 817

Japan, 1,322

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

Brazil,1,357

Indonesia, 2,472
Russian Federation,
2,030

4

Per Capita Emissions
19.8

Per Capita GHG emissions in 2014 (tCO2eq)

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

3.62.5

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

5

Emission and Temperature rise

• RCP2.6 (41～72%‍reduction‍in‍2050)‍“Likely”‍achieves‍the 2 degree target• RCP4.5(24～38%‍reduction‍in‍2050)‍“More‍unlikely‍
than‍likely”
Source: IPCC AR5, WG3, SPM, Table SPM.1

6

-50% by 2050

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

7

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

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

9

Mitigation Options (Non-energy)• Capturing GHG: Carbon capture and storage (CCS)• In powerplant and steal furnace• Waste management: Reduce CH4 from landfill and CO2 fromfossil 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 deforestation10

Transport

Business

130+ options
Lifestyle
Forestconservation

New/Renewable
EnergyTown/buildings
11How to choose?
“Marginal‍Abatement‍Cost‍(MAC)”‍curve‍(Japan,‍2020)

Source: Hibino (2010) Japan's Marginal Abatement Cost Curve Analysis and Mitigation Measures12

Wide & Low is better!
Cost per unitof GHG
reduction
Reduction
potential
13

Insulated house

Efficient electric device incommercial sector

14

Your cost is income of someone else.

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

15

What to consider?
Potential

Certainty

Cost

Co-benefit(Ancillarybenefit)

Risk

Socialacceptance16

What to consider?
Potential

Certainty

Cost

Co-benefit(Ancillarybenefit)

Risk

Socialacceptance17

Co-benefitEnergy
security

Transportconvenience

Air pollution
abatement

LandscapeSaving landfill
siteConservingresource

Employment

Access toenergy

Fuel poverty

18

What to consider?
Potential

Certainty

CostCo-benefit(Ancillarybenefit)

Risk

Socialacceptance19Social acceptance: Landscape20

“Low-carbon society scenarios”• Scenario: future image, computer-aided stories• Alternative future societies achieving climate goals• Not‍“Prediction”‍!
• “Back-casting”

21

Back-casting Approach
Target year

VisionRoadmap
Present

22

Socio-economicindicators
Energy demand
GHG emissions
LC measuresSchedule of measures
Cost to implement measures
GHG emissions reductions
Ancillary benefit of measures

ScenarioBasic ofGHG emission Projection

23

GHG emissions

Baseline
Baseyear

PolicyTime24

CO2 emissions from energy use
CO2 emission =Drivingforce

25

Energyservicedemandx

Energydemandx

Driving
force

CO2emissionx

EnergyservicedemandEnergydemandCO2 emissions from energy use
CO2 emission =Driving
force

26

Energyservicedemandx

Energydemandx

Driving
force

CO2emissionx

EnergyservicedemandEnergydemandEnergy service :Utility provided by using energy
Example:Watching TV
Lighting a room
Cooling of spaces
Transporting one person by 10km
Producing iron & steel products27Drivingforce

Energyservicedemandxx

Drivingforce

Energyserviceintensity

28

EnergydemandCO2emissionx

EnergyservicedemandEnergydemandEnergyefficiency

CO2
intensity

Driving
force

29

x

Energyserviceintensityx

Energyefficiency

xCO2
intensity

Driving
forcexEnergyserviceintensityx

Energyefficiency• Population and/or household• GDP by industry• Commercial floor area• Number of workers• Number of passenger trips by mode
• Tons of freight transported
30

x

CO2
intensity

Drivingforcex

Energyserviceintensityx

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

31

CO2
intensity

Driving
forcexEnergyserviceintensityx

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

32

CO2
intensity

Drivingforcex

EnergyserviceintensityxEnergyefficiency

xCO2
intensity• Share of fuels for cooking• Share of fuels for vehicles• Share of energy sources for power generation• Efficiency of coal/gas fired-powerplant

33

In Baseline & Policy Scenarios
Driving forcex

Residential
Urban household
Rural household

Commercial
Wholesale & RetailRestaurant & Hotel
Professional services
Public services

Industries
Primary industries
Manufacturing
Construction

Transport
Passenger
Freight

34

Energy service
intensityx

Energy efficiency

Residential & Commercial
Air conditioning, Cooking
Water heating, Lighting
OthersIndustriesIndustrial boiler, Industrial motor
Furnace, Others

Transport
Passenger cars, Bus, Train
Motorbike,
Freight carsx

CO2 intensity

Demand sideElectricity
Natural gas
Gasoline, Coal
Biomass

Supply side
Oil, Coal,
Natural gas
Hydro energy
Nuclear energy
Photovoltaic
Wind power

Simulation by “Integrated Modelling”
Export by goods

IO
analysis

Investment

Population

Output byindustry

Household size

Government expenditure
Import rate
Input coefficient matrix

Output ofcommercial industry

Output ofmanufacturingindustry

Population

Commercialbuilding floorareaFreighttransportdemandPassengertransportdemand

Number ofhousehold

Private consumption
Floor area per output
Energy service demand per
driving force

Fuel share
Energy end-use device share

Modal share

Final energy demand

Energy efficiency (CPG)

Energy demand(DPG)

Central power generation (CPG)

Fuel share (CPG)
Transmission loss (CPG)

Energy demand (CPG)
Primary energy supply

Endogenousvariables

Freight generation peroutput
Transport distance

Energy service demand

Energy efficiency DPG

Exogenous variables
Parameters

Modal share

Energy efficiency

Energy end-use device energyefficiency

Dispersed power generation(DPG)

Trip per person
Trip distanceOwn use (CPG)
CO2 emission factor
Carbon sink

CO2 emssions

35

Integration of all emission sectors
Economy anddemography• Population• Production• Transport• Population• Production• Population

Wastemanagement• Waste toenergy

Energy• Agri-waste• Biofuel• Wood demand

Agriculture• Residue• Fuel wood demand• Food & feeddemand• Crop production• Livestock
population• Biofuel production

Biofuel• Fuel crop

• Wood production• Degraded anddeforested areaForestry

Land-use36

LCS scenario with Integrated ModelingA case in Malaysia
Population
HouseholdGDP
Per capita GDP
Gross output
Primary
Secondary
Tertiary
Passenger
transport
Freighttransport

37.3
9.3
1,601
43.0
4,929
97
2,175
2,657

2020
/2005
1.3
1.4
2.0
1.6
2.0
1.5
1.6
2.5

2030
/2005
1.4
1.6
3.1
2.2
3.1
1.8
2.4
4.2

315

359

1.9

2.1

Bill. pass-km

150

214

1.6

2.3

Bill. t-km

2005

2020

2030

26.1
5.8
509
19.5
1,604
55
920
629

32.8
8.2
996
30.4
3,135
84
1,507
1,544

169
92

MillionMillionBill. RM
1000.RM
Bill. RM

Projected output by 26 sectors
5,000

Public Services
Other Private Services
Education, Research & Development
Accomodation & Restraunts
Wholesale & Retail
Real EstateFinance & Insurance
Transport Services
Water Works
Electricity & Gas supply
Construction
Other Manufacturing Products
Transport Equipments
Electric and Electronic Equipments
General Machinery
Other Metal Products
Iron & Steel
Cement, Ceramic, Stone & Cray Products
Chemical Products
Petrolium Refinery & Coal Products
Paper & Pulp
Textiles & Wearing ApparelFood, Drink & Tabacco Products
Other Mining
Oil and Gas Mining
Agriculture, Forestry & Fishing

4,500

4,000

3,500

Bill. RM

3,000

2,500

2,0001,500

1,000

500

3802005

2020

2030

Tertiary
industries

Secondaryindustries

Primaryindustries

Projected transport volume

Passenger transport

Freight transport

400

200350BicycleWalk

250

Two wheelers
200Vehicle
100

Train

150
100

Bus50Vehicles

50002005

39

Train

150

Bill. t-km

Bill. pass-km

300

2020
BaU

2030
BaU

2005

2020

2030

LCS scenario with Integrated Modeling
A case in Malaysia• GHG emissions
BaU

CM1

CM2

800

Others700

LULUCF

600

Agriculture
Waste

500

MtCO2eq

Fgt. Transport
Pass. Transport

400

Industry

300

Commercial
Residential

200

40

Periods between projected years were interpolated linearly.

2030

2025

2020

2015

2010

2005

2030

2025

2020

2015

2010

2005

2030
2000

2025

2020

2015

2010

2005

2000

02000

100

Emission intensity (GHG emission per GDP)
-22%

0.7
0.6

from 2005 from 2005
0.62

0.5

kgCO2eq/RM

-40%

0.52

0.53

0.4

0.43

0.41

0.3

0.31

0.2

0.21

0.21

2030
CM12030
CM2

0.1
0.0
2000
(NC2)

2005

2020
BaU

2020
CM12020
CM2

2030
Bau

41

Per capita GHG emission
21
19.5

18

tCO2eq

15

16.1

129

12.4
9.4

10.2

9.5

9.5

9.5

2030
CM12030
CM26302000
(NC2)

42

2005

2020
BaU2020
CM12020
CM22030
BauContribution to emission reduction in 2020
CM1CM2Others
1%

Others2%Agriculture1%

Forestry&Landu
se18%

EEI in demand
sectors
38%

Waste
18%

Modal shift
4%43

Forestry&Landu
se29%

Agriculture
1%
Renewableenergy8%

EEI in power
supply
11%

Waste
7%

Modal shift
5%

Renewableenergy11%

EEI in demand
sectors
32%

EEI in power
supply14%

Indonesia Scenarios
GHG emissions
6

エネルギー
Energy

5.3

51.7

AFOLU
GtCO2eq

BaU: Business as usual
CM1: Current policy
CM2: Current policy + Biofuel
CM3: CM2 + utilizing abandoned land

4

2.7

32

1.9

1.7

2.0

2.0

1.9

1.0

1.2

1.0

1.0

1.0

0.9

0.9

BaU

CM1CM2

CM3

1.6
10

3.5

0.3

2005

2020

3.3

3.2

3.1

0.9

1.1

1.0

2.1

2.1

CM2

CM3

2.4

BaU

CM1

2050
44

Biofuel had adverse impact
2200

GHG emission in 2020

MtCO2eq

2100
2000

2,006

2,047

1900
1800
1700

1,907

+42MtCO2eq bybiofuel

1600

CM1CM2

CM3
45

Deforestation for biofuel production
increase total GHG emissions
Decomposition of emission change from CM1CM2

エネルギー
Energy971004150

MtCO2eq

CM3

土地利用転換Land-use change

4118

泥炭火災・酸化Peat fire

0
合計
Total
-50-100(73)(73) (66)(99)

46

Summary• LCS scenario can support policy making for longterm mitigation goals• Appropriate mitigation options should be chosenconsidering cost, effectiveness, co-benefit and risk
• Modeling can compare different options byquantifying there potentials

47