Modeling Energy Demand andDeforestation Measures for a Sustainable Future

Jayant Sathaye
Lawrence Berkeley National Laboratory
Berkeley, CA
IASA-RITE International Symposium
Global Warming and Sustainable Development
18 February 2008
International Energy Studies

Total Global Greenhouse Gas Emissions
Increased by 70 % (1970 – 2004)

Carbon Dioxide Is the Largest Contributor

International Energy Studies

IPCC AR4, 2007: WG III Summary for Policy Makers
Singificant Potential for Demand-side Efficiency Improvement:
Largest Potential is in the Buildings Sector

Note:• Sectoral estimates are based on bottom-up studies• Estimates do not explicitly include non-technical options, such as lifestyle changes.
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Selected Models that
Represent Energy Demand Technologies• AIM (Asia Pacific Integrated Model) -- Bottom-up/Hybrid• AMIGA (All-Modular Industry Growth Assessment Modeling System) -- Hybrid• BEAR (Berkeley Energy and Resources -- California) -- Top-Down/Hybrid• CIMS (Canada) – Hybrid Model• COBRA -- LBNL (Global) -- Bottom-up• DNE21+ (Global) – Top-down/Hybrid• MARKAL (MARKet Allocation) -- Bottom-up Hybrid• MiniCAM (US) -- Bottom-up model/structure (OBJECT) integrated into a
Top-Down (MiniCAM) Integrated Assessment Model• NEMS (US) – Bottom-up Hybrid• Review based on secondary information and interviews with somemodelers in April 2007
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Representation of end-use technologies:
Some key issues• An advantage of bottom-up and hybrid models is that they
permit evaluation of non-price policies and programs- Standards and labels for appliances for example• Policy and programmatic costs, however, are not explicitly
considered in most models- Quantification of market failures- Transaction costs


LBNL study shows that these are less than $4 / t CO2 for
CDM type projects• Further most such models do not evaluate- Non-energy benefits- Analyze life cycle (LCA) costs and benefits
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Quantification of Market Failures:
IEA Report -- Mind the Gap(US, Japan, Netherlands, Norway, Australia+)•% of US households and energy use affected by split incentives
and asymmetric information that are characteristics of a
Principal Agent Problem•

Two transactions (Jaffe and Stavins, 1994):- Tenant and landlord-

Builder and buyerLandlords may not be able to recover all of the value of efficiency
investments in the form of higher rents, where renters pay fuel bills,
and tenants who make these investments in cases where thelandlord pays the energy bill may not be able to get reduced rents
Home builders may have difficulty conveying the benefits of energy
efficiency technologies to prospective buyers because thesetechnologies and their future energy use consequences are notobservable

Consequence is that some markets or portions thereof
may be isolated from energy price signals
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Classification of
End Users for US Residential Sector
Cannot Choose
End-User

Can Choose Technology

Technology

Direct Energy

Case N:

Case E:

Payment

No Problem

Efficiency Problem

Indirect Energy

Case U&E:

Case U:

Payment

Usage and Efficiency Problem

Usage Problem(Utilities incl. in rent or aflat fee)Primary Data Sources: Residential Energy Consumption Survey,
American Housing Survey, National Association of Home Builders, Energy Star, etc.

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Quantification of PA Market Failures
Results: % of US households and energy use
affected by the Principal Agent Problem•-

Refrigerators – 33% and 25%-

Space heating – 52% and 48%-

Water heating – 69% and 66%-

Lighting – 5% and 2.3%•

The affected four end-uses account for about
25% of US primary residential energy use•

Energy savings may be a lower percentage if
regulatory policies (standards for instance)
already require higher efficiency levels
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Representation of PA Market Failure in a Model•

Suggested approach:---Quantify impact of principal agent and lack of
information problems-

Isolate the segment of energy use by each enduse that is affected by the above problems
-Change model parameters for this segment
•Particularly important for sector-focused policies intransition scenarios
Elasticity values, discount rates, policy and program
costs, other transaction costs

Currently exploring approach for US NEMS and
MARKAL models
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Cost of Conserved Energy: Accounting for Changes in
Capital, Labor and Material Costs

I ⋅q + M
CCE =
S
d
q=
(1 − (1 + d ) − n )where:CCE = Cost of Conserved Energy for the energy efficiency
measure, in $/GJ
I = Capital cost ($)
q = Capital recovery factor
M = Annual change in labor and material costs ($)
S = Annual energy savings (GJ)d = discount raten = lifetime of the conservation measure (years)

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US Steel Industry Cost of Conserved Energy:
Other Benefits
Waste

EmissionsOperation & MaintenanceUse of waste fuels, heat, gas

Reduced dust emissions

Reduced need for engineering
controls

Reduced product waste

Reduced CO, CO2, NOx, SOxemissions

Lowered cooling requirements

Reduced waste water

Increased facility reliability

Reduced hazardous waste

Reduced wear and tear on
equipment/machinery

Materials reduction

Reductions in labor requirements

Production

Working Environment

Other

Increased product output/yields

Reduced need for personal
protective equipment

Decreased liability

Improved equipment
performance

Improved lighting

Improved public image

Shorter process cycle times

Reduced noise levels

Delaying or Reducing capital
expenditures

Improved product quality/purity

Improved temperature control

Additional space

Increased Reliability in
Production

Improved air quality

Improved worker morale

US Steel Industry Supply Curves: Accounting for
Changes in Four Categories of Benefits (previous slide)
Benefits double cost effective energy efficiency potential to 19%
21

Cost of Conserved Energy ($/GJ)
Discount Rate = 30%

18Annual Cost-Effective Primary Energy Savings
15

Excluding Non-Energy
Benefits: 1.9 GJ/tonne

Including Non-Energy
Benefits: 3.8 GJ/tonne

12difference: 1.9 J/tonne,
approximately 168 PJ/year

9631994 Weighted Average Primary Fuel Price ($2.14/GJ)

0
Cost Curve With Changes in Energy Costs-3

Cost Curve with Changes in Energy and other Benefits-60
Source: Worrell et al. (2003)

1

2

3
4
Energy Savings (GJ/tonne)

56Effect of Accounting for Changes in Other Benefits on
Cost-Effectiveness and Ranking of Measures
With Energy (E) Benefit Only
MeasureInj. of NG – 140
Coal inj. – 225
Coal inj. – 130
DC-Arc furnace
Process control
Scrap preheatingThin slab casting
Hot charging
FUCHS furnace
Adopt cont. cast
Tw in shell
Oxy-fuel burners
Bottom stirring
Foam y slag

With Other Benefits

CCE

Rank

Cost-

CCE

Rank

Cost-

($/GJ)(of 47)

Effective?

($/GJ)(of 47)

Effective?

3.1
3.9
4.4
5
5.6
6.7
8.5
8.9
12.7
14.3
16.6
17.4
20.5
30.1

19
22
23
26
27
31
35
36
37
39
40
41
45
46

NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO

-0.5
1
0.1
-1.3
-2.1
-0.6
1.9
5.3
-3.5
-3.5
3.3
-5.5
-2.4
7.2

8
23
11
6
5
7
27
35
3
2
30
1
4
40

YES
YES
YES
YES
YES
YES
YES
NO
YES
YES
NO
YES
YES
NO

NOTE: These cost of conserved energy (CCE) and cost-effectiveness calculations are based on a
discount rate of 30% and an average primary energy price of $2.14/GJ.

International Energy Studies

Life-Cycle Analysis: Energy Use and GHG Emissions for
50 Products Manufactured in California
Life-Cycle Energy Consumption and GHG Emissions of Two Generic PC Systems
Life-Cycle

Primary Energy (MJ/PC)

GHG (kg CO2/PC)

Stage

CPU+CRT

CPU+LCD

CPU+CRT

CPU+LCD

Raw Materials Acquisition

1964

2231

139

289

Manufacturing

22595

5735

533

570

Use

7544

5125

330

224

End-of-Life

-633

-277

-39

-18

31470

12814

963

1065

Total

High manufacturing energy
consumption of PC with CRT monitor
due primarily to CRT glass
manufacturing.
Manufacturing GHG emissions of PC
with LCD exceed those of PC with
CRT monitor due primarily to SF6emissions during LCD module
manufacture.

Life-Cycle Energy Consumption and GHG Emissions Occurring within California
Life-Cycle

Primary Energy (MJ/PC)

GHG (kg CO2/PC)

Stage

CPU+CRT

CPU+LCD

CPU+CRT

CPU+LCD

Raw Materials Acquisition

18

18

1

1

Manufacturing

257

257

17

17

Use

7544

5125

330

224

End-of-Life

22

10

1

0.6

7841

5410

349

243

Total

Energy consumption and GHG emissions for
PC manufacture in California are low due tooffshore production of CRT monitors, LCDs,
and many CPU components.
At end-of-life, PC landfilling and PC
demanufacturing occur in California but
recycling “credits” occur elsewhere.

Primary sources: 1) Masanet E., Price L., de la Rue du Can S., Brown R., and E. Worrell. 2004. Optimization of Product Life Cycles to Reduce Greenhouse Gas
Emissions in California. California Energy Commission, PIER Energy-Related Environmental Research. 2) U.S. EPA. 2001. Desktop Computer Displays: A LifeCycle Assessment.

14International Energy Studies

How much additional land area will be planted or
avoided from being deforested in response to C price path?
GCOMAP: A Dynamic Partial Equilibrium Economic Model
•

•

•

•

Since 1990, LBNL has
developed bottom-up forestry
sector models

DATA

GCOMAP was developed
using this expertise and data
combined with global andOECD data•Forested area
•Planted and deforested land•Maximumsuitable land area
•Opportunity cost of land
•Land price supply curve

Model represents forest sector
market dynamics; based oninvestment theory, andassumes perfect foresight•Biomass yield•Rotation period•Biomass and soil carbon•Timber product output and life
•Non-timber product output•Product demand and supply

Includes 10 regions, adeforestation and 2 forestation
options, and tracks carbon in 6
pools annually

GCOMAP Model
Structure:
3 Modules

Carbon pricescenario (2000-2100)•Planting anddeforestation costs –fixed and annual•Timber andnon-timber product prices

Land-use
ModuleAnnualland use change

Annualland use change
and land price
Economicparameters

Monetary
Costs and Benefits
ModuleReference and Mitigation Scenarios

Biomass andCarbonStock Change
ModuleLand and
Carbon Gain
(2000-2100)

Annual productoutputSocial Welfare
Change: Forest Sector(2000-2100)

Mitigation Scenario Only

15

International Energy StudiesSathaye et al. The Energy Journal Special Issue 2006

Global Net Sequestered Forestry Carbon andReduced Deforestation Emissions (Cumulative to date)Potential for carbon emissions reduction and sequestration in forestry(Carbon Price: $75 + $5 / yr; capped at $275 / t C in 2050)

100.0

300.0
C-gain through reduced emissions (Deforestation)

250.0

Carbon price

80.0

200.0
Total C-gain

60.0
40.0

150.0
C-gain through sequestration (Forestation)

100.0

20.0

50.0

0.0

0.0
2010

2020

2030

2040

2050

2060

2070

2080

2090

C a rb o n P ri c e $ / tC

C u m u l a ti v e c a rb o n g a i n * (G t
C)

120.0

2100

Year
* Carbon gain refers to the cumulative difference betw een a mitigation and reference scenario by a given year

16

International Energy Studies

Carbon choke price to theoretically stop deforestation(i.e., C price > opportunity cost) varies across regions••

Feasibility of stopping deforestation complicated by many
barriers.
Carbon choke price to theoretically halt deforestation depends
on opportunity cost of land and products– Timber and agricultural products fetch higher prices than land orother products– Higher the timber and agricultural revenue higher the carbon pricerequired to reduce or avoid deforestation
RegionCarbon choke price totheoretically stop
deforestation ($/ t C)

Africa$ 39

Central America$ 127

South America$ 147

Rest of Asia (Asia without
China and India, incl. PNG)

$ 281

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17

Net Sequestered Forestry Carbon andReduced Deforestation Emissions by Region(Cumulative to Date)
8.0 Gt C in 2010100%

113.2 Gt C in 2100
Africa_Forestn
Africa_Deforestn

Africa Deforestation

SAmerica_Forestn
SAmerica_Deforestn
RoAsia_Forestn

Samerica Deforestation

60%

RoAsia_Deforestn
CAmerica_Forestn
CAmerica_Deforestn

40%

USA
RoAsia Deforestation

20%

EU
Oceania
Russia
India
China

-20%

21
00

20
90

20
80

20
70

20
60

20
50

20
40

20
30

20
20

0%
20
10

Cumulative C-gain (%)

80%

Year

18

International Energy Studies

Baseline Setting:
How to model sharp fluctuations in base year deforested area?
Brazil Example
Annual Deforested Area in the Amazon
35,00030,000Sq. km25,00020,00015,00010,000

5,000

0
1988

1993

1998

2003

19

International Energy Studies

Source: INPE, Brazil

Offset credit exports (positive) and imports (negative)by region (Mt CO2)
In order to meet Annex I assumed 2020 emissions targets(EU, Canada, and Japan 20% and US 15% relative to 2020 Base Case)
1000

500

Annex B0
CDM regions

AfricaSouth-East Asia

Central America

South America

-500

-1000

-1500

Deforestation_lowBase [EU++]
Deforestation_highBase [EU++]-2000

Anger and Sathaye (2008)

Two-way Relationship Between Climate
Change and Sustainable Development
A. Climate policy can have positive or
negative effects on other factors-- Ancillary benefits or co-benefits

B. Non-climate development policies caninfluence GHG emissions as much as
climate-specific policies-- Requires mainstreaming climate change indecision-making

21

International Energy Studies

Other effects of climate mitigation (examples)
OPTIONSSYNERGIES

TRADEOFFS

Energy: efficiency,
renewables, fuelswitching• air quality• supply security• employment• costs (efficiency)• particulate emissions(diesel)• biodiversity (biofuels)• costs (renewables)

Forestry: reduce
deforestation, planttrees• soil protection• water management• employment• biodiversity (deforest.)• biodiversity(plantations)• competition foodproductionwaste: landfill gas
capture, incineration• health & safety• ground water• employment• energy advantages

pollution• costs
22

International Energy Studies

Development path as important as specificclimate mitigation policies
Development
path with HIGH
baseemissions

Development
path with LOWemissions23International Energy Studies

Non-climate policies can influence GHG
emissions as much as climate-specific policies
Sectors

Non-climate policies -- Candidates
for integrating climate concerns

Possible influence(% of global emissions)

Macro-economy

Taxes, subsidies, other fiscal policies

All GHG emissions (100 %)Forestry

Forest protection, sustainable management

GHGs deforestation (7%)

Electricity

Renewable energy, demand management,
decreasing losses transport,/distribution

Electricity sector emissions(20 %)

Oil-imports

Diversification energy sources/decrease
intensity -> enhance energy security

GHGs from oil product imports(20 %)

Insurancebuildings,
infrastructure

Differentiated premiums, liability conditions, GHG emissions buildings,
improved conditions green products
transport (20 %)Bank lending

Strategy/policy, lending projects accounting
for options emission limitations

Notably development projects(25%)

Rural energy

Policies promoting LPG, kerosene andelectricity for cooking

Extra emissions over biomass(<2 %)
24

International Energy Studies

3 Ways to Broaden Climate Policies(Mitigation and Adaptation)“Climate first”

International
negotiations

Statefrom climate to development policy

from global agreement to local action

from government to governance“Development
first”

Local andsector actions

All actors (state,market, civilsociety)
25

International Energy Studies

Mitigation and adaptation:synergies and trade-offs
Actions decreasing
Mitigation→ GHG emissions,increasing sinks,
protecting C pools
Adaptation↓
Actions decreasing
exposure andsensitivity to
climate change
Actions increasing
exposure andsensitivity to
climate change

Actions increasing GHG
emissions, decreasing
sinks, destroying C
pools

Synergies, e.g.
increased water
efficiency, erosion
control, cool roofs
Trade-offs mitigation(“new vulnerabilities”),
e.g. climate-sensitive
biofuels

Trade-offs adaptation(“adaptive emissions”),
e.g., air conditioning,
irrigation
Actions leading to nonsustainable
development, e.g.
deforestation
26

International Energy Studies

Conclusions• Detailed technology representation provides insight andunderstanding of technology and fuel mix choices• Accounting for principal agent problems and other market failures isimportant and will provide better insights for types of climate policies
that will be effective• Inclusion of non-energy benefits reduces net costs, changes ranking
of options, and increases emissions reduction potential• Accounting for life cycle impacts is important for a comprehensive
estimate of energy and GHG emissions• Reducing deforestation can be achieved at a relatively modest cost,
although the large baseyear uncertainty affects value of exported
carbon credits• Mainstreaming climate mitigation in development decisions withclimate consequences is essential for a low-emissions path toemergeInternational Energy Studies

Thank you
Jayant Sathaye
Web Site: http://ies.lbl.gov

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