Energy Systems Determinants 1:
Demand
86025 Energy Systems Analysis Arnulf Grubler

Former US DOE chair
86025 Energy Systems Analysis Arnulf Grubler

86025 Energy Systems Analysis Arnulf Grubler

• Demand quantities: income, price, lifestyles, infrastructure,..
• Demand qualities: availability, income, price, comfort, “(in-)convenience”,…
• Quantities and qualities interact!
• “Modernization” indicator: quantity/quality of energy, e.g. noncommercial, traditional biomass use
(cow-dung, residues, wood)
86025 Energy Systems Analysis Arnulf Grubler

Traditional Fuel Use and Demographic Indicators
140 7
120
100
6
5 infant mortality, deaths per
1000 life births female life-expectancy, years
80 4
60 3 male-female life expectancy gap, years
40 2
20 1 total fertility rate, children/woman
0
<20 20-40 40-60 60-80 >80 percent non-commercial in total energy use
0
Source: WEA, 2000, p. 53
Source: WEA 2001
86025 Energy Systems Analysis Arnulf Grubler

Europe 10,000 BC
China 100 BC
Europe 1300
England 1880
Japan 1990
USA 2000 food household production transport services
IIASA-WEC
C1 Scenario
0 50 100 150 200
GJ per capita per year
250
Source: Modified from V. Smil, 1991.
300

Mapping Energy Access
Final Energy per Capita vs Population Density AD 2000
Source: Chirkov&Grubler, IIASA, 2007.
86025 Energy Systems Analysis Arnulf Grubler

Energy Use Distribution of Indian
Households 1998-99
Source: S. Pachauri, IIASA, 2006.

India – Per Capita HH (Direct) Energy Use vs. Income:
Useful, Final and Hypothetical (with non-commercial fuel efficiencies)
Σ: Efficiency is biggest contributor to human welfare gains
25000
Hypothetical final if used with non-commercial fuel efficiencies
20000
15000
10000
Final energy
Useful energy
5000
0
<500 500-1000 1000-1500 1500-3000 3000-4500 4500-6000
HH income Rupees per year
>6000
Data: TERI, 1995.
86025 Energy Systems Analysis Arnulf Grubler

India - Primary Direct and Indirect Household
Energy Use Per Capita (1)
Average - All India
29%
19%
7%
45%
Indirect food
Indirect non-food
Direct non-commercial
Direct commercial
20
16
12
8
4
0
Average - Rural & Urban
RURAL URBAN
Direct commercial
Direct non-commercial
Indirect non-food
Indirect food
Source: S. Pachauri, IIASA, 2006.

India - Primary Direct and Indirect Household
Energy Use Per Capita (2)
39
36
33
30
27
24
21
18
15
12
9
6
3
0
Bottom
Rural
Middle
Rural
Top
Rural
Bottom
Urban
Middle
Urban
Indirect food Indirect non-food
Direct non-commercial Direct commercial
Top
Urban
Source: S. Pachauri, IIASA, 2006.

India – Fuel Use Structure of Urban and Rural Households vs. Income
Dung
Charcoal
LPG
Wastes
Soft coke
Electricity
Rural Urban
Wood
Kerosene
Data Source: TERI, 1995.
100
80
60
40
20
0
<3000 3000 - 6000 6000 - 12000 12000 - 18000
Household income (rupees per year)
86025 Energy Systems Analysis
>18000
Arnulf Grubler

Western Europe (average)
• 13,000 $ PPP income
• ~ 2.5 toe final energy
• Floorspace: 40 m 2
• Residential energy: .8 toe
• Industry energy: 1 toe
• Transport energy: .7 toe
• Passenger-km (cars #):
10,700 (.74)
• Ton-km (trucks #):
3,400 (.24)
Latin America (average)
• ~5,000 $ PPP income
• ~ 1 toe final energy
• Floorspace: 10 m 2
• Residential energy: .5 toe
• Industry energy: .3 toe
• Transport energy: .2 toe
• Passenger-km (cars #):
4,700 (.21)
• Ton-km (trucks #):
2,000 (.09)
Data characteristic for 1990s
86025 Energy Systems Analysis Arnulf Grubler

Primary Energy Use and Income: Path Dependence
10
7
6
9
8
3
2
5
4
1
0
0
1800
1850
1900
1925
1950
1975
1995
5000
USA
1800-1998
UK
1800-1998
Austria
1922-1995
Japan
1900-1998
10000 15000
Data: Butschek, 1997; Fouquet & Pearson, 1998;
Grubler, 1998; Martin, 1988 & JStO, 1998.
20000
GDP (1990 US$) per capita
25000 30000
86025 Energy Systems Analysis Arnulf Grubler

Energy Use & Wealth: OECD Past and
IIASA-WEC and IPCC Scenarios for DCs
5
4
3
2
1
0
0
10
9
8
7
6
1800
1850
1900
1925
1950
1975
1995
5000
IIASA-WEC
SRES
A1
A2
B1
B2
10000 15000
UK
1800-1998
20000
GDP (1990 US$) per capita
1800-1998
Austria
1922-1995
25000
USA
Japan
1900-1998
30000
86025 Energy Systems Analysis Arnulf Grubler

Energy Demand:
The Economist’s Perspective
• Income growth, e.g. US real-term per capita income:
+2%/yr (AFTER inflation) since 1900 = a Factor >7!
• Elasticity of demand with respect to:
-- income
-- energy prices (incl. taxes!)
-- different for different income groups, fuel types, etc.
• Biggest impacts: Income growth, cost reductions, quality improvements
• Rate of time preference: consumption ”impatience”
(discounting)
• Tradeoffs, e.g. transportation: income – price – time (air vs. car travel)
Reminder: elasticity:

>0 = % change of A per % change of B,
0>
 <1 called “inelastic”;  >1 called “elastic” e.g. income elasticity:

= +0.7 = 1% income growth

+0.7% demand e.g. price elasticity:

= -0.3 = 1% price growth
 –0.3% demand

Household Ownership (% of HH with) 1978 to 1985
(78-85 growth = colored)
TV
Refrigerator
86025 Energy Systems Analysis
Washer
Vaccum cl.
Arnulf Grubler

Cost Declines in Refrigerator Costs in US
Source: OTA, 1991.
On example of cost declines + quality improvements (efficiency) see Bill Nordhaus example. of Light https://classesv2.yale.edu/access/content/group/fes83026_f06/readings/nordhaus_lighting_1998.pdf

Consumption Impatience: Discounting
• Preference to consume now rather than later
• Incentive to save (consumption deferral): interest rate
• A bet:
I give you 1 $ today, or will put 2.3 Million $ in a trust fund to be paid out to your descendents in 300 years (a Yale story).
What would you prefer?*
• Different discount rates: social < entrepreneurial (ROI) < < individual consumption
* If you prefer 1$ today then your rate of time preference >5% (often too high for climate cost benefit assessments)

Denmark – Distribution of Discount Rates
Source: Harrison, Lou& Williams
AmEconRev., 2002
86025 Energy Systems Analysis Arnulf Grubler

Implict Discount Rates vs. Income: Purchase of
Air Conditioners in US
Source: Hausmann, 1979.
HH income,
US$(1994)/yr
12,000
20,000
30,000
50,000
70,000
100,000
Implicit discount rate, %/yr
89.0
39.0
27.0
17.0
8.9
5.1
86025 Energy Systems Analysis Arnulf Grubler

Energy Demand:
The Industrial Ecologist’s Perspective
• Product/service orientation
• “Cradle-to-grave” accounting: Net energy analysis (direct+indirect energy requirements)
• How to deal with structural change?
• How to deal with multi-factor productivity?
86025 Energy Systems Analysis Arnulf Grubler

US- Energy per $ Value Added
(TJ per Million $, energy embodiment, 1992 I-O data)
Source: Carnegie Mellon Univ. www.eiolca.net
Direct energy Indirect energy
Product fertilizer passenger cars hotels semiconductors real estate agents computer&data services
On-site Energy Transport Other Total supply sectors
130.4
1.2
7.6
3.7
3.2
1.4
6.6
6.4
147.8
12.6
2.9
0.9
0.8
0.2
5.4
3.3
2.4
1.2
0.5
0.5
0.3
0.3
1.9
2.7
1.2
1.1
10.7
7.4
4.7
3.0
Note product and value orientation:
Energy embodied in car vs. total energy use over lifetime of car
Energy $ per VA $: industry vs. services (energy price differences)
86025 Energy Systems Analysis Arnulf Grubler

Carbon Intensity of Products/Services
(2 digit SIC level) Source: Marland&Pippin, 1990.
86025 Energy Systems Analysis Arnulf Grubler

At home
Time
10 9 hrs
835.5*
Energy
( final)
10 9 kgoe kgoe/hr
236.6
0.28
At work
Services
291.1
183.5
660.0
152.0
279.0
#
2.27
0.83
Travel 107.6
2.59
Total 1417.7
1328.4
0.94
* Excluding sleeping time #Passenger travel only, rest of transportation accounted for “at work”
86025 Energy Systems Analysis Arnulf Grubler

(cumulative percentage distribution)
86025 Energy Systems Analysis Arnulf Grubler

Energy – Time – Information: Intensity of Products/Activities
Working time = 0
Energy
Real estate
Asphalt
Communication
Chemical products
Paints
Iron & steel
Radio/TV broadcasting
Plastics
Paper Metal products
Drugs
Engines / turbines
Construction
Textiles Food
Entertainment
Shoes
Restaurants
Agricultural services
Source: D. Spreng, 1993.

Economic Structural Change
(based on Kuznets, 1971)
86025 Energy Systems Analysis Arnulf Grubler

Energy Demand:
Social Science Perspectives on Value and
Lifestyle Changes
• Given: Hierarchy of needs (Maslow) economists (action
 revealed preferences?)
• Constructed: Preferences “discovered” in process of establishing social relations (Mary
Douglas) cultural theory
(perceptions
 preferences
 actions?)
• Generational change: Succession of cohorts
(e.g. Nathan Keyfitz) demographers, “cross-over” scientists
86025 Energy Systems Analysis Arnulf Grubler

(based on: Lebergott, 1993)
86025 Energy Systems Analysis Arnulf Grubler

86025 Energy Systems Analysis
Typology of
“Valueists
”
Along 2
Dimensions of
Social
Relations
&
Associated
Myths of
Nature
Source: M. Thompson based on M. Douglas and
P. Timmerman
Arnulf Grubler

N. Keyfitz, 1992.

N. Keyfitz, 1992.

Germany: Car Ownership by Gender and Age Cohorts
Source: Buttner&Grubler, 1995.
86025 Energy Systems Analysis Arnulf Grubler

Germany: Car Ownership of Female Age Cohorts
Source: Buttner&Grubler, 1995.
86025 Energy Systems Analysis Arnulf Grubler

Scenarios of Car Diffusion for a United Germany:
Greens are Outnumbered by Greys!!
3 Scenarios:
Constant 1990 Rates, Trend, Green Generation
1990: 79 Million Germans
35 Million Cars (26% female owners)
2030: 77 Million Germans (70 by 2050)
30 Million cars (24% female owners)
38 Million cars (36% female owners)
33 Million cars (41% female)
86025 Energy Systems Analysis Arnulf Grubler

86025 Energy Systems Analysis Arnulf Grubler

Percent Change since 1970 in US Automobile CO
2
Emissions and Driving Forces
86025 Energy Systems Analysis Arnulf Grubler

• Impacts = Population x
Affluence x
Technology
• Widely used decompositional technique*
• Component growth rates additive: e.g. POP 1%/yr, GDP 3%/yr, E/GDP -1%/yr
= GDP/POP 2%/yr, Energy 2%/yr
• See previous car emissions example
C (emissions) = gallons fuel use gal = gal/miles x miles/vehicle x vehicle/people (“empty seats”) x people x
ε
(adjustment for increasing SUV share), canceling out all elements: gal=gal = identity
• Assumes variables are independent!
Beware of fallacy of spatial aggregation (POP growth in
India, Car growth in US lumped together in global IPAT)!
*See e.g. Ausubel&Waggoner, 2002; and review of Chertow, JIE, 2001.
86025 Energy Systems Analysis Arnulf Grubler