Trends in energy intensity indicators
Economic Analysis of
End-use Energy Intensity in Australia
May 2012
Nhu Che and Pam Pham
1
Che, N. and Pham, P., 2012, Economic analysis of end-use energy intensity in Australia, BREE,
Canberra, May.
© Commonwealth of Australia 2012
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Acknowledgements
The authors would like to thank to Quentin Grafton (BREE) for valuable guidance and comments on the report and in the development of the project. The authors are also grateful Arif Syed, George Stanwix and Tom Shael (BREE) for helpful comments and discussions on the report. Thanks also goes to Louise Vickery and Roger Coogan (the
Department of Resources, Energy and Tourism) and to policy analysts at the Department of
Environment, Water, Heritage and the Arts; the Department of Climate Change and Energy
Efficiency; and the Bureau of Infrastructure, Transport and Regional Economies for valuable discussions.
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Foreword
A focus of the Australian Government’s energy policy is to deliver clean and sustainable energy. Important contributors to this goal are cost-effective improvements in energy efficiency or the reduction in energy intensity — the amount of energy used for a given amount of economic activity. Lower energy intensity can promote energy conservation and help to deliver low-cost greenhouse gas abatement.
Energy intensity can be influenced by many factors including energy prices, technological developments, household preferences and government policies. To support on-going improvements in energy intensity, Australian, state and territory governments have developed a variety of frameworks within broader energy and environmental policy strategies.
As part of the Bureau of Resources and Energy Economics (BREE’s) on-going work on energy in Australia, the Economic Analysis of End-use Energy Intensity in Australia provides trends of energy consumption, energy intensity and factors underlying these trends (activity, structural and energy efficiency changes) over the period
1989–90 to 2009–10. The results are analysed for the six economic segments of the economy: the manufacturing, services, mining, agricultural, transport and residential sectors. Where data is available, sub-sector analyses are undertaken to assess the causal determinants on changes in energy intensity from 1989–90 to 2009–10.
The results provide a ‘lens’ to interpret the key drivers and changes in energy use in
Australia over the past two decades. The findings in this important publication should prove invaluable to policy makers, to analysts and, indeed, to anyone who wishes to be better informed and to understand the energy transformations underway in the Australian economy.
Quentin Grafton
Executive Director/Chief Economist
May 2012
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Contents
5
6
Figures
Figure 1: Decomposition of change in energy consumption .............................................................. 10
Figure 2: Scope of the report ............................................................................................................. 11
Figure 3: Shares in total energy consumption by economic sector ................................................... 12
Figure 4: Trends in energy-GDP ratio and the composite energy intensity indicator in Australia ..... 13
Figure 5: Trends in composite energy intensity indicators in the Australian economy ..................... 13
Figure 6: Energy consumption in the manufacturing sector, 1989–90 to 2009–10 ........................... 16
Figure 7 : Decomposition of change in energy consumption in the manufacturing sector ................ 16
Figure 8: Growth in activity in the manufacturing sector, 1989–90 to 2009–10 ............................... 17
Figure 9: Trends in composite energy intensity indicators in the manufacturing sector ................... 18
Figure 10: Yearly change in energy consumption of manufacturing due to the efficiency effect ... 18
Figure 11: Energy prices and composite energy intensity index for the manufacturing sector ...... 19
Figure 12: Energy consumption in the services sector, 1989–90 to 2009–10 ................................. 21
Figure 13: Decomposition of change in energy consumption in the services sector ...................... 21
Figure 14: Growth in activity in the services sector, 1989–90 to 2009–10 ..................................... 22
Figure 15: Trends in composite energy intensity indicators in the services sector ......................... 23
Figure 16: Yearly change in energy consumption of services due to the efficiency effect ............. 23
Figure 17: Energy price and composite energy intensity index for the services sector .................. 24
Figure 18: Energy consumption in the mining sector ...................................................................... 27
Figure 19: Decomposition of change in energy consumption in the mining sector ........................ 28
Figure 20: Trends of intensity and yearly change in energy consumption in the mining sector ..... 28
Figure 21: Yearly change in energy consumption of mining due to the efficiency effect ............... 29
Figure 22: Energy prices and energy intensity in the mining sector ................................................ 30
Figure 23: Gross value added of the major mining subsectors ....................................................... 30
Figure 24: Energy consumption in the agriculture sector ............................................................... 32
Figure 25: Decomposition of change in energy consumption in the agriculture sector ................. 33
Figure 26: Trends of intensity and yearly change in energy consumption in the agricultural sector
33
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Figure 27: Yearly change in energy consumption of agriculture due to the efficiency effect ......... 34
Figure 28: Energy price and energy intensity in the agricultural sector .......................................... 34
Figure 29: Impact of climate condition to increase energy intensity of grain production .............. 35
Figure 30: Movement of energy consumption in the transport sector, 1989–90 to 2009–10 ........ 37
Figure 31: Energy consumption in passenger transportation, 1989–90 to 2009–10 ...................... 38
Figure 32: Energy consumption in freight transportation, 1989–90 to 2009–10 ............................ 39
Figure 33: Decomposition of change in energy consumption in the transport sector .................... 40
Figure 34: Trends in composite energy intensity indicators in the transport sector ...................... 41
Figure 35: Yearly change in energy consumption of transportation due to the efficiency effect ... 41
Figure 36: Energy prices and composite energy intensity index for the transport sector .............. 42
Figure 37: Trends in energy consumption of the residential sector ................................................ 45
Figure 38: Energy consumption in household energy uses, 1989–90 to 2009–10 .......................... 46
Figure 39: Energy consumption in household appliances ............................................................... 47
Figure 40: Number of households and average occupied stock area per household ..................... 47
Figure 41: Decomposition of change in energy consumption in the residential sector .................. 47
Figure 42: Trend of intensity and yearly change in energy consumption in the residential sector 49
Figure 43: Yearly energy consumption because of the efficiency effect in household energy uses50
Figure 44: Yearly energy consumption due to the efficiency effect in the residential sector ......... 51
Figure 45: Residential energy prices and composite energy intensity for the residential sector ... 52
Figure 46: Household appliance ownership ................................................................................... 53
Tables
Table 1: Summary of coverage and variables in the manufacturing sector ...................................... 15
Table 2: Summary coverage and variables used in the services sector ............................................ 20
Table 3: Summary of coverage and variables used in the transport sector ...................................... 37
Table 4: Summary of coverage and variables used in the residential sector .................................... 44
Table 5: Sector classifications used in Economic Analysis of End Use Energy Intensity in Australia 59
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Acronyms and abbreviations
ABARES Australian Bureau of Agricultural and Resource Economics and Science
ABS Australian Bureau of Statistics
APEC
BITRE
Asia-Pacific Economic Cooperation
Bureau of Infrastructure, Transport and Regional Economics
BREE
COAG
DEWHA
DCCEE
Bureau of Resources and Energy Economics
Council of Australian Governments
Department of the Environment, Water, Heritage and the Arts
Department of Climate Change and Energy Efficiency
DRET
IEA
PJ
Department of Resources, Energy and Tourism
International Energy Agency
Petajoules
Explanatory note:
‘The study period’ refers to the period from 1989–90 to 2009–10.
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1. Introduction
This report provides detailed analyses of end use energy intensity in key parts of the
Australian economy including: the agriculture, mining, manufacturing, services, transport and residential sectors over the period 1989–90 to 2009–10. The report identifies the key factors affecting energy consumption change in each sector.
The method of analysis uses an approach that is well developed in the literature and previously adopted by Ang and Liu (2001), Ang et al. (2003) and Sandu and Petchey
(2009). The results provide analysis of energy intensity for the 21 years period 1989–
90 to 2009–10. Change in energy use during 1989–90 to 2009–10 is decomposed into: (i) the activity effect, which is based on the output or level activity of the economic sector; (ii) the structural effect based on changes in the composition of activity; and (iii) the efficiency effect based on changes in energy intensity. A change in energy consumption can be expressed as the sum of these three factors, and movements in each effect over time can also analysed separately (see Figure 1).
Figure 1: Decomposition of change in energy consumption
Change in energy consumption
Activity effect Intensity effect
Structural effect Efficiency effect
This report provides an analysis of changes in energy intensity for major parts of the
Australian economy, including: (i) manufacturing, (ii) services, (iii) mining, (iv) agriculture, (v) transport and (vi) residential sectors. Energy consumption based on activity, structural and efficiency effect is decomposed separately for each industry.
The scope of the report is outlined in Figure 2, with a focus on end-use energy consumption in the manufacturing, services, mining, agriculture, transport and residential sectors.
Data used in this study are sourced from ABARES (2011a and 2011b); Schultz and
Petchey (2011); the Australian Bureau of Statistics (ABS); the Department of the
Environment, Water, Heritage and the Arts (EES 2008); Apelbaum Consulting Group
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(2009); and the Bureau of Infrastructure, BITRE (2009 and 2011) and BREE data sources.
Scope of the report Figure 2:
Primary energy supply energy supply
Coal mine
(coal)
Oil well
(crude oil)
Natural gas primary energy
Renewable
Energy conversion
Electricity generation
Petroleum refining
Natural gas processing
Coke& and
Briquettes manufacturing
Energy end-use sectors final energy
Manufacturing (10 sub sectors)
Services (7 subsectors)
Mining
Agriculture
Transport
Passenger
- Motor vehicles (cars, motorcycles and buses)
- Rail (heavy rail, light rail)
- Shipping (ferries and coastal)
- Air (domestic aviation)
Freight
- Motor vehicles (LCVs, articullate and rigid trucks)
- Rail (heavy rail, light rail)
- Shipping
- Air
Residential
- Space heating
- Space cooling
- Water heating
- Cooking
- Lighting
- Appliances (10 appliances)
Note: Sectors covered in this report.
Production of liquefied natural gas is included in the mining sector.
Consumption of coal and liquid fuels are not covered in the residential sector.
The following chapters analyse trends in energy consumption and factors underlying these trends (activity, structural changes and efficiency) for the major Australian economic sectors over the period 1989–90 to 2009–10.
Economy-wide trends in end use energy intensity are provided in Chapter 2. A review of energy intensity trends in each end use sector of the economy is given in Chapters 3 to 8. The methodology, mathematical framework and industry classifications used in the report are detailed in the appendices.
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2. End use intensity in Australia
Key Findings
The aggregate energy-GDP ratio of the end use sectors in the Australian economy declined at an average rate of 1.3 per cent a year between 1989–90 and 2009–10.
The Australian composite energy intensity indicator derived from energy intensities of individual end-use sectors declined at an average rate of 0.2 per cent a year between 1989–90 and 2009–10.
The transport sector accounts for the largest share of the final energy consumption in Australia, followed by the manufacturing sector. Energy intensity in these sectors had decreased over the study period.
There has been an upward trend in energy intensity of the mining sector. This result, however, needs to be treated with caution because a lack of subsector data for the mining sector means that the effect of structural changes in the mining sector cannot be analysed fully.
Two common ways of measuring aggregate energy intensity include: the energy-GDP ratio and a composite energy intensity indicator that aggregates energy intensity measures across sectors of the economy (see Figure 3). The energy-GDP ratio is the most basic aggregate intensity indicator. For the end use sectors covered in this report, the energy-GDP is the ratio of total final energy consumption to gross value added. The energy-GDP ratio for Australia as a whole declined at an average annual rate of 1.3 per cent over the period 1989–90 to 2009–10 (Figure 4).
Figure 3: Shares in total energy consumption by economic sector
The energy–GDP ratio provides information on how many units of energy units are required for a unit of gross value of production. Thus, a declining trend of energy-
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GDP ratio implies that an equivalent amount of a given energy demand is able to generate greater value added.
Figure 4: Trends in energy-GDP ratio and the composite energy intensity indicator in Australia
The composite energy intensity indicator computes economy-wide energy intensity.
It is obtained by aggregating energy intensities derived for individual sectors or subsectors (see Appendix A for more detail). Several countries, including Canada
(NRC 2006) and the US (OEERE 2005), have used this indicator as an aggregate measure of energy intensity.
Composite energy intensity in the Australian economy declined at an average rate of
0.2 per cent a year, compared with 1.3 per cent for the energy-GDP ratio (Figure 5).
As shown in Figure 5, the services, manufacturing, transport and residential sectors are the main sources of the decline of energy intensity for the Australian economy.
Figure 5: economy
Trends in composite energy intensity indicators in the Australian
Note: These trends in energy intensity do not imply any weighting of energy consumption by sector.
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3. Energy intensity in the manufacturing sector
Key Findings
In 2009–10, the manufacturing sector accounted for around 12 per cent of economic output (in real gross value added terms) and 31 per cent of final energy consumption in Australia. In terms of energy consumption as a share in total energy use of the industry, the major sub industries are basic nonferrous metal (34 per cent); chemical and associated products (19 per cent); and iron and steel (16 per cent).
Energy consumption grew at an average rate of 0.9 per cent a year between 1989–90 and 2009–10. The chemical and associated products, and the wood, paper and printing subsectors, have been the fastest growing sectors in terms of energy consumption, with average annual rates of increase of 2.6 per cent and 1.8 per cent, respectively.
Between 1989–90 and 2009–10 energy consumption in the manufacturing sector increased by 34 petajoules. The largest contributor to the increase in energy consumption was the chemical and associated products subsector, which accounted for 88 petajoules of the energy consumption increase over the study period, while other sectors such as iron and steel decreased.
The activity effect resulted in energy consumption increasing by 254 petajoules over the period 1989–90 to 2009–10, with the chemical and associated products subsector accounting for 110 petajoules of the energy consumption increase.
The structural effect or shifts of activity from the iron and steel and basic nonferrous subsectors (higher energy intensity) to the lower energy intensity subsectors (such as the chemical and associated products, the food, beverage and tobacco and the machinery and equipment subsectors) reduced energy consumption over the study period by 111 petajoules.
During 1989–90 and 2009–10 the efficiency effect contributed to reduced energy consumption by 109 petajoules and resulted in an average annual reduction in energy use of 0.7 per cent.
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Observed trends in energy consumption
The manufacturing sector is the second largest user of final energy in the Australian economy after the transport sector. The key 10 sub-sectors in manufacturing are described in Table 1. In 2009–10 the sector accounted for around 12 per cent of economic activity (output in real gross value-added terms) and 31 per cent of final energy consumption.
Table 1: Summary of coverage and variables in the manufacturing sector
Food
Textile
Wood
Chemical
Non metallic mineral
Iron and steel
Non-ferrous metal
Other metals
Machinery
Other manufacturing
Activity value-added value-added value-added value-added value-added value-added value-added value-added value-added value-added
Structure share of total output share of total output share of total output share of total output share of total output share of total output share of total output share of total output share of total output share of total output
Intensity energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added
Energy consumption in the manufacturing sector increased over the period 1989–90 to 2009–10 with an average annual growth rate of 0.9 per cent. However, from
1997–98 to 2007–08 energy consumption in this sector increased at a faster annual growth rate of 1.4 per cent. Most of the energy consumption increase has been in the nonferrous metal subsector and the chemical and associated products subsector.
The composition of and growth in energy consumption in the manufacturing subsectors, are presented in Figure 6.
The largest consumer of energy consumption within the manufacturing sector was non-ferrous metals. During 1989–90 to 2007–08, this subsector was the fastest growing energy user in the sector, with energy consumption increasing at an average annual rate of 2.5 per cent. However, since 2008–09 energy consumption in this subsector has been declining because of considerable decreases in activity
(measured in terms of gross value-added). The share in energy consumption of this subsector increased from 29 per cent in 1989–90 to more than 36 per cent in 2007–
08, but fell to around 26 per cent in 2009–10.
The second largest consumer of final energy within the manufacturing sector is the chemical and associated products subsector, with an energy consumption share of around 23 per cent in 2009–10. Energy consumption in this subsector increased continuously at an average annual rate of 2.6 per cent during the study period.
Energy consumption of the iron and steel subsector, which accounts for around 18 per cent of final energy consumption in this sector in 2009–10, decreased at an average annual rate of 1.1 per cent from 1989–90 to 2009–10, but did increase slightly between 2007–08 to 2009–10.
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Figure 6:
10
Energy consumption in the manufacturing sector, 1989–90 to 2009–
Decomposition of changes in energy consumption
Figure 7 summarises the changes in energy consumption and its factored components (activity, structural and efficiency effects) in the manufacturing sector over the period 1989–90 to 2009–10.
Figure 7 : Decomposition of change in energy consumption in the manufacturing sector
Changes in energy consumption in the manufacturing sector between 1989–90 and
2009–10 were strongly associated with changes in activity, which contributed to increased energy consumption by 254 petajoules. Activity (output in value-added terms) in the manufacturing industry overall increased at an average annual rate of
1.5 per cent (see Figure 8). The chemical and associated product and the non metallic subsectors were the fastest growing subsectors, with an average annual growth rate of 3.7 per cent and 3.4 per cent, respectively. By contrast, activity in the textile subsector decreased continuously at an average annual rate of 2.3 per cent over the study period. Since 2009–10 there has been a significant decrease in energy
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consumption in the iron and steel and the nonferrous subsectors as a result of reduced production in these subsectors.
The iron and steel and the non ferrous subsectors are high energy intensity subsectors that comprise about 45 to 50 per cent of energy consumption, respectively.
Thus, any shifts between the iron and steel and the non ferrous subsectors and other manufacturing subsectors, such as the chemical and associated product subsector, would affect the energy intensity of the manufacturing sector as a whole. Between
1989–90 and 2009–10 the structural change effect has caused a decrease of energy consumption in this sector by 111 petajoules.
The efficiency effect in the manufacturing sector resulted in a decrease in energy use of 109 petajoules between 1989–90 and 2009–10. Compared with 1989–90, declining energy consumption associated with the efficiency effect in the food, beverage and tobacco (93 petajoules) and chemical, non-metallic and iron and steel subsectors (70 petajoules) was offset by increases in energy consumption in the nonferrous metal subsector in 2009–10.
Figure 8: Growth in activity in the manufacturing sector, 1989–90 to 2009–10
Trends in energy intensity indicators
Figure 9 presents the trend in composite energy intensity in the manufacturing sector and its major subsectors. Energy intensity declined slightly throughout the study period at an average annual rate of 0.7 per cent. However, increases in energy intensity in the nonferrous metallic subsector after 2002–03 offset the energy savings from decreases in energy intensity in the non-metallic mineral, chemical and associated products and also the food, beverage and tobacco subsectors.
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Figure 9: Trends in composite energy intensity indicators in the manufacturing sector
Note: These trends in energy intensity do not imply any weighting of energy consumption by sector.
Figure 10 shows the yearly change in energy consumption associated with the efficiency effect. Overall, the efficiency effect contributed to decreases in energy consumption during study period. However, in 2009–10, the efficiency effect caused an increase in energy consumption of around 100 petajoules. This was largely a result of relatively stable energy consumption in the nonferrous metallic subsector coupled with a substantial decline in gross value added.
Figure 10: Yearly change in energy consumption of manufacturing due to the efficiency effect
150.0
100.0
50.0
-50.0
-100.0
-150.0
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Factors affecting energy intensity
The key factors affecting energy intensity in the manufacturing sector are energy prices, structural change, technology improvements and government policies.
Cornillie and Fankhauser (2004) argued that the two main factors influencing energy efficiency are higher energy prices and new technologies which increase the productivity of each unit of energy.
Birol and Keppler (2000) also noted that higher energy prices can induce improvements in energy usage efficiency, thereby lowering energy intensity.
Figure 11 shows the movements of prices and energy intensity in the manufacturing sector between 1989–90 and 2009–10. The period 1989–90 and 2007–08 is associated with increase in energy prices and corresponded with a decline in energy intensity in the manufacturing sector.
Figure 11: Energy prices and composite energy intensity index for the manufacturing sector
Source: Energy prices from the International Energy Agency (IEA) (2011).
Activity in high energy intensity subsectors (the iron and steel and the basic nonferrous metal) has decreased significantly since 2008–09. In particular, activity has shifted from the iron and steel and the non ferrous subsectors (high energy intensity) to the chemical and associated product subsector (low energy intensity).
This, in turn, has helped to reduce energy intensity.
Cornillie and Fankhauser (2004) argue that the progress of technology improvements of energy efficiency may have contributed to a decline in energy intensity. Over the study period some of the technology improvements that may have improved energy efficiency use in this sector include the use of highly efficient motors and boilers, and the removal of unnecessary equipment or maintenance programs to repair old or failing equipment to optimise the efficiency of the system (IEA 2007b).
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4. Energy intensity in the services sector
Key Findings
In 2009–10, the services sector accounted for around 3 per cent of economic output (in real gross value added terms) and 7 per cent of final energy consumption in Australia. The major energy user is the wholesale and retail trade subsector that accounts for 42 per cent of energy consumption in the service sector.
Energy consumption in the services sector grew at an average rate of 2.9 per cent a year between 1989–90 and 2009–10. The fastest growing energy users in this sector were the communication and the water supply, sewerage and drainage services subsectors, with an average annual rate of
5.1 per cent and 4.7 per cent, respectively.
Energy intensity in the services sector declined by 0.7 per cent per year during 1989–90 to 2009–10.
The activity effect in the services sector resulted in an increase in energy consumption by 166 petajoules over the period 1989–90 to 2009–10, half of which is attributed to the whole sale and retails trade subsector.
The structural effect of a shift of activity from the water supply, sewerage and drainage and the wholesale and retail trade subsectors (higher energy intensity) to the communication and finance subsectors (lower energy intensity) reduced energy consumption over the study period by 14 petajoules (structural effect).
The efficiency effect resulted in energy savings of 23 petajoules between
1989–90 and 2009–10. Over the entire period, the efficiency effect resulted in an average annual reduction in energy use of 1.0 per cent over the same period.
Observed trends in energy consumption
In 2009–10, the services sector accounted for around 3 per cent of the total economic output (in real gross value-added term) and 7 per cent of final energy consumption in Australia. The key seven sub-sectors in the services sector are listed in Table 2.
Table 2: Summary coverage and variables used in the services sector
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Water supply
Wholesale and retail trade
Communication
Finance
Government and defence
Education
Accommodation
Activity value-added value-added value-added value-added value-added value-added value-added
Structure share of total output share of total output share of total output share of total output share of total output share of total output share of total output
Intensity energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added energy/value-added
Figure 12 shows the composition of and growth in energy consumption in the services subsectors. Energy consumption in the sector has shown an increasing trend over the study period, with an average annual growth rate of 2.9 per cent. The key sources of the increase in energy consumption are from the wholesale and retail trade subsector, which contributed 60 petajoules of the increase in energy consumption over the period 1989–90 to 2009–10.
The largest consumer of final energy consumption within the services sector was the wholesale and retail trade subsector, which accounted for 42 per cent of total energy consumption in 2009–10. During the period 1989–90 to 2009–10, energy consumption in this subsector grew by an average annual growth rate of 3.2 per cent.
Figure 12: Energy consumption in the services sector, 1989–90 to 2009–10
Decomposition of changes in energy consumption
Figure 13 summarises the changes in energy consumption and the component effects (activity, structural and efficiency effects) in the services sector over the period 1989–90 to 2009–10. Total final energy consumption increased by 123 petajoules. Most of this increase was in the wholesale and retail subsector. In total this subsector contributed 60 petajoules to the overall increase in energy consumption in the services sector.
Figure 13: Decomposition of change in energy consumption in the services sector
21
change in energy consumption 123 activity effect 166 structural effect -14 efficiency effect -23
-50 50 100 150 200
Changes in energy consumption in the services sector between 1989–90 and 2009–
10 were strongly influenced by changes in activity. Increased activity alone would have resulted in higher energy consumption of 166 petajoules. Most of this increase occurred in the wholesale and retail trade subsector.
Activity measured as output in value-added terms in the services sector overall increased at an average annual rate of 3.5 per cent over the period 1989–90 to
2009–10 (see Figure 14). The communication subsector was the fastest growing energy user, with energy use consumption growing at an average annual rate of 5.1 per cent. The finance and the wholesale and retail trade subsectors also grew strongly at an average annual rate of 3.8 and 3.2 per cent, respectively.
Figure 14: Growth in activity in the services sector, 1989–90 to 2009–10 communication finance wholesale and retail accommodation education government & defence water supply total
2.0
4.0
6.0
average annual growth rate, 1989-90 to 2009-10
8.0
Between 1989–90 and 2009–10, the efficiency effect resulted in a 23 petajoules decrease in energy consumption in the services sector. The largest contributor to this decrease was a 19 petajoules reduction in energy consumption in the education, health and community services subsector.
The decrease in energy consumption driven by the structural effect was 14 petajoules. This reduction of energy consumption resulted from a decrease in
22
activity of the water supply, sewerage and drainage and the wholesale and retail trade subsectors (with higher energy intensities) and an increase in the communication and finance subsectors (with lower energy intensities) (see Figure
13).
Trends in energy intensity indicators
Figure 15 shows that energy intensity in the services sector decreased continuously from 1989–90 to 2007–08, but increased slightly from 2008–09 to 2009–10 because of increasing in energy intensity in the wholesale and retail trade subsector. Energy intensity in the education and finance subsectors decreased continuously over the entire period.
Figure 15: Trends in composite energy intensity indicators in the services sector
1.2
1.1
1.0
0.9
0.8
0.7
0.6
1989-90=1 wholesale and retail education finance total
Note: These trends in energy intensity do not imply any weighting of energy consumption by sector.
Figure 16 shows the changes in energy consumption driven by the efficiency effect for each year between 1989–90 and 2009–10. In 2008–09, a fall in the energy efficiency effect resulted in an increase in energy consumption by 21 petajoules. This lower energy efficiency is associated with an increase in activity of the wholesale and retail trade subsector where energy intensity is relatively higher.
Figure 16: Yearly change in energy consumption of services due to the efficiency effect
23
30
25
20
15
10
5
PJ
0
-5
-10
Factors affecting energy intensity
The key factors affecting energy intensity in the services sector include energy prices, structural changes within the sector, technology change and government policies.
Figure 17 presents the movements of prices and energy intensity in the services sector between 1989–90 and 2009–10. Higher real energy prices provide an incentive for energy to be used more efficiently. In turn, this leads to a reduction in energy used to produce the same output, a decline in energy intensity. While energy prices have increased over the study period, energy intensity in the services sector has only declined since 1999–2000.
A shift from more energy-intensive services to less energy-intensive subsectors (e.g., a shift from the wholesale and retail trade subsector to the communication subsector) also reduced energy intensity for the sector as a whole.
Figure 17: Energy price and composite energy intensity index for the services sector
24
Source: Energy prices from the International Energy Agency (IEA) (2011).
Birol and Keppler (2000), Hang and Tu (2007) and Sanddu and Petchey (2009) note that the other key factors that may affect energy intensity in the services sectors include technological advancement and government policies. Such policies include targets of energy efficiency in commercial and industrial buildings, in the building codes, the adoption of the Energy Star and Energy Rating systems for appliances and equipments, and mandatory energy performance standards.
25
5. Energy intensity in the mining sector
Key Findings
In 2009–10, the mining sector accounted for around 11 per cent of economic output in terms of real gross value added and 13 per cent of final energy consumption in Australia.
During the period 1989–90 to 2009–10 energy consumption increased by
349 petajoules with an average growth rate of 5.7 per cent a year.
The activity effect of the mining sector increased energy consumption by
199 petajoules between 1989–90 and 2009–10.
The efficiency effect increased energy consumption by 150 petajoules between 1989–90 and 2009–10.
Due to the lack of subsector data for the mining sector the impact of the structural changes on the energy consumption is not available. Thus, the results of energy intensity of the mining sector should be treated as a preliminary analysis.
Energy intensity in the mining sector grew at an annual rate of 2.3 per cent over the period 1989–90 to 2009–10.
26
The Australian mining sector is a highly energy-intensive industry that accounted for
11 per cent of gross value added and 13 per cent of final energy consumption of the
Australian economy in 2009–10. A lack of sub-sector data for the mining sector for the period 1989–90 to 2009–10 prevents analysing the structural effects in the mining sector. As a result of this data limitation the energy intensity results should be used with caution and treated as a preliminary analysis.
Observed trends in energy consumption
During the period 1989–90 to 2009–10 final energy consumption in the mining sector grew at an average rate of 5.7 per cent a year. Figure 18 shows energy consumption in the mining sector. Over the 21 years period energy consumption in the mining sector more than tripled and increased by about 350 petajoules. Most of this growth in energy consumption coincided with the resources commodities boom that began 2002–03 and led to very large increase in mining commodity prices.
Figure 18: Energy consumption in the mining sector
600
500
400
300
200
100
Decomposition of changes in energy consumption
Figure 19 summarises the changes in energy consumption and its factored components (activity and efficiency effects) in the mining sector over the period
1989–90 to 2009–10. Given the high energy intensity in the oil and gas or exploration sectors the structural changes within this subsector almost certainly have had an important impact on mining energy consumption. Unfortunately, due to insufficient data at subsector level for the period 1989–90 to 2009–10, these structural effects can not be analysed at this time.
As a result of the resource commodity boom, activity (output in value-added terms) in the mining sector increased strongly and continuously at an average annual rate of
3.2 per cent over this period. An increase in activity alone would have raised energy consumption of 199 petajoules. However, a negative efficiency effect also
27
contributed to the increase in the sector’s energy consumption. Overall, the efficiency effect caused an increase in energy consumption in the mining sector by
150 petajoules from 1989–90 to 2009–10.
Figure 19: Decomposition of change in energy consumption in the mining sector change in energy consumption activity effect 199
349 efficiency effect 150
100 200 300 400
Trends in energy intensity indicators
Energy intensity of the mining sector increased throughout 1989–90 to 2009–10, except in 2000–01 (see Figure 22). On average, energy intensity grew at an annual rate of 2.3 per cent over the entire period.
Figure 20: Trends of intensity and yearly change in energy consumption in the mining sector
1.0
0.8
0.6
0.4
0.2
1.8
1.6
1.4
1.2
1989-90=1
20
10
0
-10
-20
60
50
40
30 change in energy consumption (right axis) energy intensity
A negative energy efficiency resulted in increased energy consumption during 1989–
90 to 2009–10 (see Figure 21). A possible reason for this trend is that higher energy intensity is associated with an increase in the use of energy for exploration activity
28
and the need to exploit deeper and lower grade ores—particularly base metals such as copper, nickel, lead and zinc. In addition, the sharp rise in production of relatively energy-intensive liquefied natural gas (LNG) may have contributed to the increase in energy intensity in the sector in recent years.
Figure 21: Yearly change in energy consumption of mining due to the efficiency effect
Factors affecting energy intensity
Figure 22 shows the movements of energy prices and energy intensity in the mining sector between 1989–90 and 2009–10. Both energy intensity and energy prices show a relative upward trend between 1989–90 and 2009–10. This indicates that the effect of energy price was not the most dominant factor influencing the trend of energy intensity in this sector. This may be explained by the fact that much higher commodity prices provided an incentive to increase mining output quickly and may have reduced the financial incentive to control energy cost if such cost controls delayed mining output expansion.
Due to a lack of energy consumption data at subsector level the structural effect in the mining sector cannot be estimated at this time. Energy intensity in the oil and gas subsector, however, is more than sevenfold higher than in other mining sector.
The gross value added of the oil and gas subsector increased substantially from
2003–04 to 2009–10 and coincided with a period of increasing energy intensity in the mining sector (see Figure 23).
29
Figure 22: Energy prices and energy intensity in the mining sector
Source: Energy prices from the International Energy Agency (IEA) (2011).
Figure 23: Gross value added of the major mining subsectors
45000
40000
35000
30000
25000
20000
15000
10000
5000
2011 0
$m coal mining oil and gas other mining support & services
30
6. Energy intensity in the agriculture sector
Key Findings
In 2009-10, the agricultural sector accounted for around 2 per cent of economic output (in real gross value added term) and 2.3 per cent of final energy consumption in Australia.
Between 1989–90 and 2009–10 energy consumption increased by 41 petajoules with an average growth rate of 3.3 per cent a year between 1989–
90 and 2009–10.
Over the period 1989-90 to 2009-10 the activity effect resulted in energy consumption in agriculture increasing by 29 petajoules.
The structural change between the plantation and the livestock subsectors over 1989–90 to 2009–10 increased energy consumption by 14 petajoules.
The efficiency effect increased between 1989–90 and 1999–2000 and reduced energy consumption by 24 petajoules in 1999-00. However, during the Millennium drought the impact of the efficiency effect declined. In
2009-10 the energy consumption saved due to the efficiency effect in agriculture was only 2 petajoules.
Energy intensity in the agricultural sector increased by 1.1 per cent per year between 2001–02 and 2009–2010 during the years of the Millennium drought.
31
Observed trends in energy consumption
The agricultural sector accounted for around 2 per cent of economic activity (output in real gross value-added terms) and 2.3 per cent of final energy consumption in
2009–10. Energy consumption in the agriculture sector increased at an average annual rate of 3.3 per cent between 1989–90 and 2009–10. In 2009–10, energy consumption in the sector increased by 41 petajoules compared with 1989–90 and was 50 per cent higher in average over the Millennium drought 2000–01 to 2009–10 than the period 1989–90 to 1999–00.
Figure 24: Energy consumption in the agriculture sector
120
100
80
60
40
20
Decomposition of changes in energy consumption
Figure 25 summarises the changes in energy consumption and the component activity and efficiency effects in the agriculture sector over the period 1989–90 to
2009–10. Changes in energy consumption in the agricultural sector during this period appear to be strongly influenced by changes in activity. The activity effect alone accounted for 71 per cent (or 29 petajoules) of the increase in energy consumption in agriculture.
Activity in this sector is measured in terms of output as gross value-added and it grew at an average annual rate of 2.9 per cent over 1989–90 to 2009–10. During the severe drought years in 2002–03 and 2006–07, activity in the sector fell before recovering in 2008–09 and 2009–10, growing at an average annual growth rate of 10 per cent and 4 per cent, respectively. Between 1989–90 and 2009–10 the activity effect in the agriculture sector resulted in an increase in energy use of 29 petajoules, while the efficiency effect reduced energy consumption by 2 petajoules.
32
Figure 25: Decomposition of change in energy consumption in the agriculture sector change in energy consumption 41 activity effect structual effect
29
14 efficiency effect -2
0.8
0.6
0.4
0.2
0.0
1989-90=1
1.4
1.2
1.0
-10 10 20 30 40 50
Trends in energy intensity indicators
Figure 26 shows that energy intensity in the agriculture sector stayed more or less unchanged over the study period. Following the approach of Che et al (2011) the energy intensity computed for the agriculture sector is adjusted for weather-related impacts.
Figure 26: Trends of intensity and yearly change in energy consumption in the agricultural sector
25
20
15
10
5
0
-5
-10 change in energy consumption (right axis) energy intensity
33
Figure 27 shows the efficiency effect reduced energy consumption in most years, especially over the period 1995–96 to 2003–04.
Figure 27: Yearly change in energy consumption of agriculture due to the
efficiency effect
Factors affecting energy intensity
According to Cornillie and Fankhauser (2004), Hang and Tu (2007) and Che et al.
(2011) the key factors that may affect energy intensity in the agricultural sector are weather factors, energy prices, technology and government policies.
Figure 28 shows the movements of energy prices and energy intensity in the agricultural sector between 1989–90 and 2009–10. The increasing trend of energy prices coincided with a slightly decreasing trend of energy intensity since 2003–04.
Figure 28: Energy price and energy intensity in the agricultural sector
34
Source: Energy prices from the International Energy Agency (IEA) (2011).
The impact of weather conditions on energy intensity in agriculture has been analysed in a study by Che et al. (2011). Their study shows that less favourable weather conditions, such as drought, contribute to higher trend of energy use in agriculture. In the case of grain production in Western Australia, for instance, an energy intensity measure was adjusted to eliminate the impacts of variations in precipitation during the grain-growing period. The found that the impact of less favourable weather conditions increased energy intensity (where 1989–90=1), as shown in Figure 29 and that during the worse drought years in the 2000s energy intensity increased substantially.
Figure 29: Impact of climate condition to increase energy intensity of grain production
0.6
0.5
0.4
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3
index
1989-90=1
35
7. Energy intensity in the transport sector
Key Findings
In 2009–10, the transport sector accounted for 6 per cent of economic output in terms of real gross value added and around 36 per cent of final energy use in Australia. About 63 per cent of energy consumed in the transport sector is associated with the movement of passengers, with the remainder accounted for by the movement of freight.
Transport energy consumption grew at an average annual rate of 1.7 per cent a year between 1989–90 and 2009–10. Over this period energy consumption in passenger and freight transport sub-sectors grew at an average annual rate of 1.5 per cent and 2.3 per cent, respectively.
The activity effect resulted in transport energy consumption increasing by
631 petajoules over the period 1989–90 to 2009–10, with passenger transport contributing 332 petajoules and freight contributing 299 petajoules of this increase.
The structural effect associated with shifts within the passenger and freight transport sectors hardly changed energy consumption over the study period. In the freight transport subsector, shifts from less to more energyintensive modes led to an increase in energy consumption of 2 petajoules.
However, this was fully offset by a movement to less energy-intensive modes for passenger transport.
The efficiency effect in the passenger transport and freight transport subsectors resulted in an average annual reduction in energy use of 1.0 per cent and 1.6 per cent, respectively. In 2009–10 the efficiency effect alone reduced energy consumption by 94 petajoules for passenger transport and
123 petajoules and freight transport.
Energy intensity in the transport sector declined at an average rate of 1.3 per cent per year over the period 1989–90 to 2009–10.
36
The transport sector comprises activities relating to the movement of passengers and freight. The transport modes covered in the analysis follow a framework devised by the Bureau of Infrastructure, Transport and Regional Economics (BITRE) (2011) and are outlined in Table 3.
Table 3: Summary of coverage and variables used in the transport sector
Passenger transport
- Motor vehicles (cars,
motorcycles and buses)
- Rail (heavy rail, light rail)
- Shipping (ferries and coastal)
- Air (domestic aviation)
Freight transport
- Motor vehicles (LCVs, articulate
and rigid trucks)
- Rail (heavy rail, light rail)
- Shipping
- Air
Activity passenger-kms passenger-kms passenger-kms passenger-kms tonne-kms tonne-kms tonne-kms tonne-kms
Structure share of total pass-km share of total pass-km share of total pass-km share of total pass-km share of total tonne-km share of total tonne-km share of total tonne-km share of total tonne-km
Intensity energy/pass-km energy/pass-km energy/pass-km energy/pass-km energy/tonne-km energy/tonne-km energy/tonne-km energy/tonne-km
Energy consumption is computed from the data sources available from ABARES
(2011) with structural adjustment for transport modes based on time-series of
APELBAUM (2009) from 1989-90 up to 2007-08. Given that there is a slight variation in values of energy consumption between APELBAUM (2009), ABARES (2011) and
BREE data sources, the energy unit (PJ) of energy consumption estimated by BREE may differ slightly to Sandu and Petchey (2009) and Petchey (2010), but the share and the trend of energy movement are consistent.
Observed trends in energy consumption
In 2009–10, the transport sector accounted for around 36 per cent of final energy consumption in Australia. The most important component of the transport sector is the passenger subsector that accounts for about 63 per cent of the energy consumed.
Energy consumption in the transport sector grew at an average annual rate of 1.7 per cent a year from 1989–90 to 2009–10. From 1989–90 to 2009–10 energy consumption in the passenger and freight transport grew continuously (see Figure
30) at an average annual rate of 1.5 per cent and 2.3 per cent, respectively.
Figure 30: Movement of energy consumption in the transport sector, 1989–90 to 2009–10
37
1600
1400
1200
1000
800
600
400
200
PJ
0 total transport passenger freight
Figure 31 shows the composition of and growth in energy consumption by the various modes of passenger transport. Passenger transport energy use is dominated by road transport that accounted for around 74 per cent of total energy use of this sector in 2009–10.
From 1989–90 to 2009–10 energy consumption of road transport increased at an annual rate of 1.1 per cent. Air passenger transport composition increased from 5 percent in 1989–90 to 25 per cent in 2009–10 of the energy consumed by passenger transport. Air transport was the fastest growing passenger mode, with average growth rate of activity of 7.3 per cent per year over the period 1989–90 to 2009–10.
Energy consumption of water transport mode also increased at a high rate of about
3 per cent a year, but the energy composition of the water passenger mode is relatively small and only accounts for 0.4 per cent of energy consumption of passenger transport.
Figure 31: Energy consumption in passenger transportation, 1989–90 to 2009–
10
Energy use in freight haulage in Australia is dominated by road transport. Over the period 1989–90 to 2009–10 the composition of energy consumption of road freight
38
transport has been relatively stable and accounted for almost 80 per cent of total energy consumption within freight transport (see Figure 31). Energy used in this transport mode grew at an average annual rate of 2.3 per cent over the period
1989–90 to 2009–10.
Figure 32: Energy consumption in freight transportation, 1989–90 to 2009–10 composition annual growth road road shipping shipping rail
2009-10
1989-90 rail air air
20 40 60 energy consumption shares
80 2 4 6 average annual growth rate, 1989-90 to 2009-10
Decomposition of changes in energy consumption
Figure 33 shows the results of the decomposition of changes in energy consumption in the transport sector. Overall, energy consumption in the transport sector increased by 416 petajoules from 1989–90 to 2009–10. Passenger and freight transport contributed to increases of 244 petajoules and 172 petajoules of energy consumption, respectively. The activity effect alone would have resulted in an increase in energy consumption of 631 petajoules. This is accounted for by growth in both the freight transport sector and the passenger transport sector.
Over the period 1989–90 to 2009–10 period the passenger transport sector grew at an average annual rate of 2.1 per cent, from 240 billion passenger-kilometres in
1989–90 to 369 billion passenger-kilometres in 2009–10. The growth of passenger activity alone would have led to an increase in energy use in the transport sector of
332 petajoules. Air was the fastest growing passenger transport mode, with average growth rate of activity of 7.3 per cent per year over 1989–90 to 2009–10.
The freight transport sector grew at an annual growth rate of 3.5 per cent from 390 billion tonne-kilometres in 1989–90 to 851 billion tonne-kilometres in 2009–10.
During 1989–90 to 2009–10, road and rail freight transport (the largest freight transport modes in terms of activity) each grew at an average annual growth rate of
2.3 per cent and 1.8 per cent, respectively. The growth of freight transport activity alone over this period would have led to an increase in energy use in the transport sector by 299 petajoules.
39
Figure 33: Decomposition of change in energy consumption in the transport sector
172
299 freight transport
-123
-3
244
332 passenger transport
-94
6
416
631 total transport
2
-217
-400 -200 change in energy consumption structural effect
200 400 activity effect efficiency effect
600 800
The structural effect among the transport modes (road, rail and air) resulted in a slight increase in energy consumption in the transport sector of 2 petajoules. The passenger transport sector contributed an increase of 6 petajoules to energy consumption, but the freight transport sector reduced energy consumption by 3 petajoules.
Compared with the base year 1989–90, the efficiency effect in the transport sector resulted in a reduction in energy use of 217 petajoules in 2009–10. Without the efficiency effect, energy consumption would have increased at an average annual rate of 2.7 per cent, compared with the actual rate of 2.1 per cent. Energy savings were made in both passenger travel (94 petajoules) and freight haulage (123 petajoules).
40
Trends in energy intensity indicators
Despite substantial variability a declining trend in energy intensity in the transport sector is observed over the period 1989–90 to 2009–10. This is despite an increase in energy intensity in the passenger transport sub-sector in the mid to late 1990s (see
Figure 34). Overall, energy intensity in the passenger transport sector declined at an average rate of 0.6 per cent a year, while energy intensity in the freight transport sector declined more rapidly at an average annual rate of 1.3 per cent.
Figure 34: Trends in composite energy intensity indicators in the transport sector
Note: These trends in energy intensity do not imply any weighting of energy consumption by sector.
The energy intensity indicator for passenger transport, as measured by energy use per passenger-kilometre, takes in to account the fuel efficiency of vehicles as well as the number of passengers in a vehicle (or occupancy). If the vehicle occupancy rate declines, energy intensity tends to increase even without changes in vehicle efficiency. Figure 35 shows the change in energy consumption driven by changes in energy efficiency for each year over the study period. The analysis suggests that freight transport made larger, more sustained energy efficiency savings compared with passenger transport.
Figure 35: Yearly change in energy consumption of transportation due to the efficiency effect
41
50
40
30
20
10
PJ -
-10
-20
-30
-40 passenger freight
Factors affecting energy intensity
Figure 36 shows the pattern of movements of the relationship between real petrol prices and energy intensity in the transport sector between 1989–90 and 2009–10. A declining trend of energy intensity in the transport sector is associated with an increase in petrol prices. However, energy intensity also shows a declining trend over periods of relative decreases in fuel prices. This suggests that other factors such as the efficiency of the engine, aerodynamics and characteristics of transport vehicles have an important influence on energy intensity. After 2001–02, following a rapid increase in energy prices, energy intensity decreased. There have been several recent technological advances that have improved the fuel efficiency of vehicles, including the development of small, highly-efficient diesel engines and improved aerodynamic design.
Figure 36: Energy prices and composite energy intensity index for the transport sector
42
Source: Energy prices from the International Energy Agency (IEA) (2011).
Note: These trends in energy intensity do not imply any weighting of energy consumption by sector.
While sales of new passenger vehicles (excluding sports utility vehicles) grew at a slightly slower rate than growth in disposable income over the period 1994–95 to
2009–10, sales of energy-intensive sports utility vehicles grew at an average rate of 9 per cent (Petchey 2010).
The Australian Government has a range of policies to improve the fuel efficiency of vehicles. As road transport is the major user of energy in the transport sector, it has received particular policy focus. Examples of existing policies include the National
Average Fuel Consumption target, which involves mandating fuel efficiency improvement targets for new motor vehicles, and the Fuel Consumption Labelling
Scheme and Green Vehicle Guide, which provide information to consumers on the energy consumption of motor vehicles (Australian Transport Council 2009). Local and state government have also introduced measures to control traffic congestion, such as road tolls, that promote increased the utilisation of existing vehicles.
43
8.
Energy intensity in the residential sector
Key Findings
In 2009–10, the residential sector accounted for around 11 per cent of final energy use in Australia. Space heating, appliances and water heating dominated energy consumption, accounting for 35 per cent, 30 per cent and 26 per cent per cent of residential energy consumption, respectively.
From 1989–90 to 2009–10 energy consumption in the residential sector grew by 41 per cent or at annual rate of 1.6 per cent. About half of the energy use increase occurred from the use of household appliances. Over the period from 1989–90 to 2009–10, Australia’s population increased by
31 per cent to 22 million. This increase alone would have resulted in energy consumption increasing by 103 petajoules due to the activity effect.
From 1989–90 to 2009–10, a structural change effect from improvements in the standard of living or an increase in average living area per person is estimated to have led to an increase in energy consumption of 138 petajoules.
The efficiency effect in the residential sector resulted in a reduction in energy use by 113 petajoules during 1989–90 to 2009–10. The largest energy saving came from more efficient energy consumption of space heating.
Energy intensity in the residential sector decreased slightly, or at an annual rate of 0.3 per cent over the period 1989–90 to 2009–10.
Observed trends in energy consumption
Energy is used for various household-related purposes, such as space heating and cooling, water heating, lighting, cooking and household appliances in the residential sector. The key energy subsectors in the residential sector are listed in Table 4 in terms of activities (space heating, space cooling, water heating, cooking and appliance) and by appliances within households.
Table 4: Summary of coverage and variables used in the residential sector
44
Space heating
Space cooling
Water heating
Cooking
Lighting
Appliances, including
- Refrigerator
- Freezer
- Washing machine
- Clothes dryer
- Dishwasher
- Television
Activity population population population population population population population population population population population
Structure floor area/person floor area/person persons/household persons/household persons/household appliances/person appliances/person appliances/person appliances/person appliances/person appliances/person
Intensity energy/appliance energy/appliance energy/household energy/household energy/floor area energy/appliance energy/floor area energy/appliance energy/appliance energy/appliance energy/appliance
- IT equipment
- Microwave
- Electric kettle
- Other appliances
Note: population population population population appliances/person appliances/person appliances/person appliances/person energy/appliance energy/appliance energy/appliance energy/appliance
Coal and liquid fuels are not covered in this report.
Cooking: includes LPG and wood used during camping and barbeque
Energy/household is adjusted for household occupancy (number of persons per household)
Overall, the residential sector accounted for around 11 per cent of final energy use in
Australia in 2009–10 and its energy consumption grew at an average annual rate of
1.6 per cent between 1989–90 and 2009–10. The data sources used in this chapter are from DEWHA (2008) for historical data and projection of energy consumption in the residential sector; ABARES, BREE and ABS.
Figure 37 shows the composition of and growth in energy consumption by household energy. More energy is used in space heating than for any other residential energy use and comprised almost 35 per cent of energy consumed in households in 2009–10. Information and Technology (IT) equipment –a component of household appliances –accounted for only 1.4 per cent of total energy use in households, but was the fastest growing energy user in the residential sector and grew at a rate of 26 per cent a year from 1989–90 to 2009–10.
Figure 37: Trends in energy consumption of the residential sector
45
500
450
400
350
300
250
200
150
100
50
PJ
0
Based on the DEWHA (2008) data of historical and projected energy consumption, it is estimated that space heating, appliances and water heating dominated residential energy consumption and respectively contributed to 35 per cent, 30 per cent and 26 per cent of overall residential energy consumption in 2009–10.
Figure 38: Energy consumption in household energy uses, 1989–90 to 2009–10
Decomposition of changes in energy consumption
In the residential sector, the activity effect accounts for change in population growth and residential occupied area. The structural effect is measured as the changes in average dwelling area per person, changes in ownership for various household appliances, including space heating and cooling equipments, and changes in household occupancy for other end uses. Energy intensity for each end use–the efficiency effect–is defined as either energy use per appliance, energy use per unit of floor area or energy use per resident.
46
Figure 39: Energy consumption in household appliances
Figure 40: Number of households and average occupied stock area per household
160
140
120
100
80
60
40
20 metres
8
7
6
5
4
3
2
1
10
9 household (right axis) average living area per household
Energy consumption in the residential sector increased by 128 petajoules from
1989–90 to 2009–10. The activity effect alone resulted in energy consumption increasing by 103 petajoules as a result of an increase in the Australian population from 17.1 million people in 1989–90 to 22.3 million in 2009–10. An increase in the number of households from 6.1 in 1989–90 to 8.6 million in 2009–10, as well as an increase in the average size of houses by floor area may be considered as a structural effect (IEA 2007a).
Figure 41: Decomposition of change in energy consumption in the residential sector
47
change in energy consumption 128 activity effect 103 structual effect 138 efficiency effect -113
-200 -100 100 200
An increase in the use of appliances associated with variations in weather may also be attributed to the activity effect. For instance, the increased use of air conditioners during a run of high average temperature years could result in an increase in activity.
However, as data on heating-degree and cooling-degree days are not available, the weather effect is not considered in this study.
The structural effect includes increases in house size and appliance ownership, and also a reduction in household occupancy, led to an increase in energy consumption of 138 petajoules.
An overall rise in the number of appliances per person–appliance ownership–is estimated to have increased energy consumption by 47 petajoules in 2009–10 relative to 1989–90. This trend was mostly driven by the increased ownership of refrigerators, televisions, lighting and IT equipment. Partially offsetting the increase in energy consumption from appliances was a structural shift away from space heating, partially explained by the increasing use of reverse-cycle air conditioning systems, or a sustained decrease in the number of heating-degree days. In addition to a shift toward more appliances, a general preference in the use of home entertainment systems (including games consoles and larger televisions) and growth in IT equipment (including computers) has contributed to an increase in residential energy consumption.
The efficiency effect in the residential sector resulted in a reduction in energy use, on average, of 1.3 per cent a year over the period 1989–90 to 2009–10. Without the efficiency effect, energy consumption would have increased at an average annual rate of 2.9 per cent instead of the actual annual rate of 1.6 per cent.
Trends in energy intensity indicators
Trends in energy intensity and changes in annual energy consumption are presented in Figure 42. The trends show that energy intensity in the residential sector decreased slightly at an annual rate of 0.3 per cent over the period 1989–90 to
2009–10.
48
The observed improvement in energy used for space heating and water heating in
Figure 43 is partly explained by the substitution away from electric hot water systems to natural gas and solar hot water systems, facilitated by the continued expansion of the natural gas network (EES 2008).
An increase in energy intensity for some end uses does not necessarily indicate lower energy efficiency of these appliances. For example, Pears (2007) and Sandu and Petchey (2009) observed that in Australia the energy intensity of the average television stock has been increasing because of a growing trend of high technology televisions (such as plasma and LCD televisions), larger screen sizes, and an increase in the number of hours of operation. The increase in energy intensity of lighting per household may be as a result from greater use of less energy efficient low-voltage halogen lamps and an increase in outdoor lighting.
Figure 42: Trend of intensity and yearly change in energy consumption in the residential sector
1.0
1.0
1.0
index
1989-90=1
1.1
1.1
1.1
1.1
1.0
1.0
10
5
20
15
0
-5 change in energy consumption (right axis) energy intensity
Figure 43 shows that in 2009–10 most of the energy savings, associated with the efficiency effect, in the residential sector were made in space heating (118 petajoules). Water heating and cooking also contributed a small part of energy saved by -0.3 petajoules and -0.4 petajoules, respectively. However, energy savings were not achieved in appliances and space cooling. Increases in energy intensity in standby power of appliances, various electrical appliances (including lighting, televisions, IT equipment and microwaves), washing machines, swimming pools and spas, and space cooling led to an additional energy requirement of 35 petajoules.
The largest increase in energy intensity is estimated to be in standby power, followed by televisions and lighting. Less energy efficiency in space cooling also led to a slight increase in energy consumption by 3.4 petajoules.
49
25
20
15
10
5
40
35
30
6
4
2
0
-2
-4
-6
-100
-120
-140
-20
-40
-60
-80
Figure 43: Yearly energy consumption because of the efficiency effect in household energy uses
5
4
3
2
1
0
-1 space heating space cooling
2
1
0
-1
-2
PJ
5
4
3 cooking water heating appliance
Figure 44 shows the change in energy consumption as a result of the efficiency effect for each year over the period 1989–90 to 2009–10. It indicates that the efficiency effect is an important factor contributing to sustainable saving in energy consumption.
50
Figure 44: Yearly energy consumption due to the efficiency effect in the residential sector
5
PJ
0
-5
-10
-15
-20
Factors affecting energy intensity
Studies by Hang and Tu (2007) Birol 2000; Cornillie and Fankhauser 2004 provided evidence that energy prices have an important impact on energy intensity.
Increasing energy prices provides a financial incentive to conserve energy to control household energy expenses. This incentive frequent can take the form of purchasing more energy efficient appliances, installing energy efficient lighting and other energy saving behaviours. In the 1990s, low energy prices in Australia (IEA 2011) were associated with a period of increasing residential energy intensity (see Figure 45).
After 2001–02, following a rapid rise in energy prices energy, energy intensity has stabilised.
51
Figure 45: Residential energy prices and composite energy intensity for the residential sector
Source: Energy prices from the International Energy Agency (IEA) (2011).
Modern energy-efficient appliances, such as refrigerators, freezers, ovens, stoves, dishwashers, and clothes washers and dryers, use significantly less energy than older appliances. The adoption of modern energy-efficient appliances should reduce energy consumption. However, these energy savings may be offset by a shift toward a higher rate of appliances ownership per household. For instance, ownership of televisions and dishwashers increased from 1.65 and 0.2 per household in 1989–90 to nearly 2 and 0.5 per household in 2009–10, respectively.
Household appear to have shifted toward more energy-intensive appliances, such as
IT equipment, larger refrigerator and large-screen televisions. For example, ownership of IT equipment increased significantly from 0.04 per household in 1989–
90 to more than 1 per household in 2009–10. Changing preferences toward more energy efficient technologies associated with a growing environmental awareness is expected to have had a downward effect on energy intensity. For instance, energy efficiency of refrigerators led to a higher level of energy saving, but ownership of refrigerators increased from 1.3 per household in 1989–90 to 1.4 per household in
2009–10 (see Figure 46).
The combination of Australia's dry climate and latitude provides a considerable opportunity for household consumption of solar energy. In 2010 solar energy contributed between 0.1 to 0.2 per cent of total electricity production in Australia
(ABS 2012). The use of solar energy by Australian households has also increased rapidly since 2005–06, supported by the introduction of government support for clean energy use in Australia.
52
Figure 46: Household appliance ownership
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
dishwashers microwaves televisions refrigerators
IT equipment
Technological improvements have been an important contributor to reduced energy consumption of many household appliances, including refrigerators and washing machines, as well as lighting, hot water systems and space conditioning systems.
However, increasing use of other technological developments, such as DVD players, set top boxes, games consoles, computers and other IT equipment, are likely to increase energy intensity per household or resident.
53
Appendix A: Methodology
This appendix reviews the method of decomposition and composite index method used in this report. To retain consistency with previous studies of energy intensity in
Australia, in this report the approach follows the method, with some minor revisions, applied by Sandu and Syed (2008) and Sandu and Petchey (2009).
Decomposition method
Previous studies by Sun (1998) and Albrecht et al. (2002) contributed to the methodology applied to energy consumption decomposition analysis, in particular in relation to the issue of perfect decomposition. Ang et al. (2003) proved that, mathematically, the Shapley decomposition is the same as the method proposed by
Sun (1998).
This report applies a similar approach used in the report by Sandu and Petchey
(2009) for energy consumption decomposition analysis (see Ang 2001 and Ang et al
2003). Changes in energy use over the period 1989–90 to 2009–10 are decomposed into three components that affect energy consumption—the activity effect, the structural effect and the efficiency effect. The decomposition technique, also known as factorisation, used in this report is the LMD I method, disaggregates changes in energy consumption into these three components. This method has a number of advantages over other decomposition methods and does not leave an unexplained or residual component.
The activity effect of an economic sector refers to the changes in energy consumption that arise solely from the changes in activity in the economy typically.
In this report activity is measured in terms of passenger-kilometres and freightkilometres for the transport sector, population for the residential sector, and gross value added for other sectors.
The change in energy consumption associated with changes in the composition of activity is referred to as the structural effect. The structural effect captures changes in energy consumption when sectors with different energy intensities grow or decline at different rates, after adjusting for growth in overall activity.
The change in energy consumption associated with the change in energy intensity of each sector is referred to as the efficiency effect. This measure provides a useful indicator of energy efficiency. However, it is not equal to energy efficiency in the strict engineering sense unless the analysis is undertaken at the most disaggregated level of the economy.
Energy consumption E for a sector with n subsectors can be expressed as:
E
n i
A
A i
A
E i
A i
(1)
54
where A is the total activity for the sector, A i
is the activity of a sector’s i th subsector and E i
is the energy consumption of the i th subsector. The second term on the righthand side gives the share of the subsector’s activity of the total sector activity and the third term gives the energy intensity of the i th subsector. By defining S i
A i
A and I i
E i
A i
, equation 1 can be rewritten as:
E
A n i
S i
I i
(2)
Equation 2 provides the basis for various energy decomposition methods (see Ang et al. (2003), Liu and Ang (2003) and Ang (2004) for comparisons of these methods).
Ultimately, of interest is in how changes in energy consumption over time can be decomposed into the three factors on the right-hand side. This decomposition can be done either additively or multiplicatively. For the additive decomposition method, each of the three components of energy consumption is expressed in absolute terms; that is, in energy units. In this report, energy consumption is measured in terms of petajoules. For the multiplicative decomposition method, each component is expressed in terms of an index. For details of the multiplicative form see Ang and
Liu (2001), Ang et.al (2003) and Ang (2004).
The additive type of the LMDI decomposition method allows us to express a given change in energy consumption of the i th subsector as the sum of a change in activity
(activity effect), a change because of shifts in structure (structural effect) and a change because of changes in energy intensity (efficiency effect):
E i
E i , T
E i , O
i
ln
A i , T
A i , O
i
ln
S i , T
S i , O
i
ln
I i , T
I i , O
(3) where the subscripts 0 and T refer to the value of the variables at the start and end of the interval of interest. The variable
i
is the logarithmic mean of energy consumption across the start and end periods and is defined as:
i
E i , T ln E i , T
E i , O
ln E i , O
(4)
Similarly, the multiplicative type of the LMDI decomposition method allows us to express a given change in energy consumption of the i th subsector as the product of an activity effect, a structural effect and an efficiency effect:
E i
E i , T
E i , O
exp
i
ln
A i , T
A i , O
exp
i
ln
S i , T
S i , O
exp
i
ln
I i , T
I i , O
(5)
Here, the variable
i
is the logarithmic mean of energy consumption across the start
0 and end T periods and is defined as:
55
i
E
i , T
E
T
E i , O
E
O
ln
ln
E i , T
E
T
ln ln E i
E
O
, O
(6)
The first term on the right-hand side of equations 3 and 5 is the activity effect, the second is the structural effect and the third is the efficiency effect. It is this third term that can be used to develop the composite energy intensity indicator. The efficiency effects derived at the subsector level can be aggregated into the sectoral composite energy intensity indicator. This sectoral indicator can be further aggregated into the economy-wide composite energy intensity indicator.
Composite index method
The composite index method is a straight forward method of calculating an aggregate energy intensity indicator as an alternative to the energy-GDP ratio. The composite energy intensity indicator is based on a bottom-up approach (Ang 2004), developed by aggregating energy intensities derived for individual sectors (or subsectors) within any level of the hierarchy. The advantage of this method is that it allows for a high degree of flexibility in the choice of activity variables used. That is, it can be used to aggregate both physical-thermodynamic and economicthermodynamic indicators into a consistent aggregate composite indicator. This approach has been used in a number of country studies, including in Canada (NRC
2006) and the US (OEERE 2005).
The composite energy intensity indicator is developed by aggregating sectoral energy intensities derived from the decomposition method. Specifically, this method aggregates the influence of the efficiency effect from the individual subsectors to approximate the energy efficiency of the whole economy.
In an additive decomposition, the composite energy intensity indicator CEII is simply the sum of the third term on the right-hand side of equation 3 for all subsectors:
CEII
n i
i
ln
I i , T
I i , O
(7)
In a multiplicative decomposition, the composite energy intensity indicator CEII is defined as:
CEII
exp
n i
i
ln
I i , T
I i , O
(8)
Further details about construction of CEIIs based on the LMDI method provided by
Ang (2004).
Several factors can affect the composite energy intensity index, including the activity measure chosen (physical or monetary), the degree of sectoral or end use disaggregation (higher level of disaggregation leads to better estimates), data
56
availability and quality. These factors must be taken into account when interpreting the results or when making international comparisons.
57
Appendix B: Sector Classification
The sector classification and definitions used in this study broadly correspond to the
2006 Australian and New Zealand Standard Industrial Classification (ANZSIC).
However, new classifications were incorporated into the latest issue of the
Australian National Accounts (ABS 2011b), the main source of activity data used in the report. In turn, this required a backward revision of all time series in the national accounts. As a result, classifications have been slightly modified for the purpose of this report is to obtain the classifications shown in Table B.
Following Petchey (2010) and to retain comparability with previous Australian end use energy intensity studies, some changes to the new ANZSIC structure have been made. These include:
finance, insurance, property and business services, which incorporates the new
ANZSIC divisions’ financial and insurance services (division K); rental, hiring and real estate services (division L); professional, scientific and technical services (division M); and administrative and support services (division N); and
education, health and community services, which incorporates education and training (division P); and healthcare and social assistance (division Q); and
accommodation, cultural and personal services, including accommodation and food
(division H); arts and recreation (division R); and other services (division S).
Additions to the ANZSIC classification to account for activities that are not classified in economic units. These changes are:
the addition of a residential sector (ANZSIC has no provision for the classification of private households consuming fuels because it is designed to classify productive activities) and various end use activities in this sector
the separation of domestic transport sector into passenger and freight activities; and
the addition of a number of transport modes for the passenger and freight transport sectors.
Some sectors are also excluded from the ANZSIC classification to represent only those sectors that consume a final form of energy. That is, the sectors that perform energy conversion activities are excluded in this report. These changes are:
the exclusion of the electricity supply (ANZSIC 361) and gas supply (ANZSIC 362) sectors; and
the exclusion of the petroleum refining (ANZSIC 1701) and petroleum and coal product manufacturing (ANZSIC 1709) subsectors from the manufacturing sector
the exclusion of coke oven operations and blast furnace operations from the iron and steel manufacturing subsector (ANZSIC 2210).
58
Table 5: Sector classifications used in Economic Analysis of End Use Energy
Intensity in Australia
Sectors/sub-sectors used in the study
Industry and services
Agriculture (including forestry and fishing)
Mining
Manufacturing and construction
Food
Textile
Wood
Chemical
Non-metallic mineral
Iron and steel (excludes coke ovens and blast furnaces)
Non-ferrous metal
Other metals
Machinery and equipment
Other manufacturing
Construction
Services
Water supply
Wholesale/retail trade
Communication
Finance, insurance, property and business
Government administration and defence
Education, health and community services
Accommodation, cultural and personal services
Transport
Passenger transport
Road
Rail
Ship
Air
Freight transport
Road
Rail
Ship
Air
Residential
Space heating
Lighting
Space cooling
Water heating
Cooking
Appliances
Refrigerator
59
ANZSIC code (2006 edition)
Division A
Division B
Division C: subdivision 11 and 12
Division C: subdivision 13
Division C: subdivision 14, 15 and 16
Division C: subdivision 18 and 19
Division C: subdivision 20
Division C: subdivision 21
Division C: group 213 and 214
Division C: class 2221-2299
Division C: subdivision 23 and 24
Division C: subdivision 25
Division E
Division D: subdivision 28
Divisions F and G
Division J
Divisions K, L, M and N
Division O
Divisions P and Q
Divisions H, R and S
Division I: subdivision 46-49 na part of group 462 part of group 472 part of group 482 part of subdivision 49 na part of group 461 part of group 471 part of group 481 part of subdivision 49 na na na na na na na na
Sectors/sub-sectors used in the study
Freezer
Washing machine
Clothes dryer
Dishwasher
Television
Microwave
Information technology equipment
Electric kettle
Other electrical appliances
ANZSIC code (2006 edition) na na na na na na na na na
60
References
ABARES 2011a, Australian energy statistics: Energy update 2009, Canberra, August.
ABARES 2011b, Australian commodity statistics 2009, Canberra, December.
ABS 2011, Australian National Accounts: State Accounts, catalogue no. 5220.0,
Canberra, November.
Ang, BW 2004, ‘Decomposition analysis for policymaking in energy: which is the preferred method?’, Energy Policy, vol. 32, pp. 1131-1139.
Ang, BW and Liu, FL 2001, ‘A new energy decomposition method: perfect in decomposition and consistent in aggregation,’ Energy Policy, vol. 26, pp. 537-548.
Ang, BW, Liu, FL and Chew, EP 2003, ‘Perfect decomposition techniques in energy and environmental analysis,’ Energy Policy, vol. 31, pp. 1561-1566.
APEC 2009a, Peer Review on Energy Efficiency in Chile: Final Report, Tokyo, April.
APEC 2009b, Peer Review on Energy Efficiency in New Zealand: Final Report, Tokyo,
April.
APEC 2010, Ministerial Statement – Fukui Declaration on Low Carbon Paths to Energy
Security: Cooperative Energy Solutions for a Sustainable APEC, Fukui, June.
Apelbaum Consulting Group 2009, Australian Transport Facts, Clayton, Victoria, May.
Australian Bureau of Statistics (ABS) 2006a, Australian and New Zealand Standard
Industrial Classification (ANZSIC), 2006, catalogue no. 1292.0, Canberra, February.
Australian Bureau of Statistics (ABS) and Bureau of Resources and Energy Economics
(BREE) 2012, Documents at the Australian Government Energy Data Forum
(unpublished).
Australian Transport Council 2009, Vehicle Fuel Efficiency Working Group: Final
Report.
Birol, F and Keppler, JH 2000, ‘Prices, technological development and the rebound effect,’ Energy Policy, vol. 28, pp. 457-469.
Bureau of Infrastructure, Transport and Regional Economics (BITRE) 2011, Australian
Infrastructure Statistics Yearbook 2011, Canberra.
Bureau of Infrastructure, Transport and Regional Economies (BITRE) 2009, Australian
transport statistics: Yearbook 2009, Canberra.
61
Che N, Grafton Q, Feldman D and Pham T 2011, ‘Energy Productivity Analysis of the
Australian Grain Industry’, Resources and Energy Quarterly–December quarter,
Bureau of Resources and Energy Economics, Canberra.
ClimateWork Australia., 2012, ‘Industrial energy efficiency data analysis project’, presentation to DRET Secretary, Drew Clarke.
Cornillie, J and Fankhauser, S 2004, ‘The energy intensity of transition economies,’
Energy Economics, vol. 26, pp. 283-295.
Council of Australian Governments (COAG) 2012, Report of energy efficiency 2011, www.coag.gov.au/reports/index.cfm (access on 26 April 2012).
Department of Climate Change and Energy Efficiency (DCCEE) 2010, Solar Hot Water
Rebate, Canberra, available at www.climatechange.gov.au/government/programsand-rebates/solar-hot-water.aspx.
Department of Environment, Water, Heritage and the Arts (DEWHA) 2008, Energy
use in the Australian residential sector 1986-2020, prepared by Energy Efficient
Strategies for DEWHA.
Department of Resources, Energy and Tourism (RET) 2011a, Draft of Energy White
Paper 2011a-Strengthening the Foundation for Australia’s energy future, RET,
Canberra.
Department of Resources, Energy and Tourism (RET) 2011b, Continuing
opportunities: Energy Efficiency Opportunities (EEO) program- 2010 report, RET,
Canberra.
Department of Resources, Energy and Tourism (RET) 2012, ‘The Energy Efficiency
Data Framework’, Energy Efficiency Data Framework, RET, Canberra.
Hang, L and Tu, M 2007, ‘The impacts of energy prices on energy intensity: Evidence from China,’ Energy Policy, vol. 35, pp. 2978-2988.
HM Treasury 2007, The King Review of low-carbon cars, London.
IEA 2007b, Tracking Industrial Energy Efficiency and CO
2
Emissions, Paris.
IEA 2011, 25 Energy efficiency recommendations: 2011 update, www.iea.org/papers/2011/25recom_2011.pdf (accessed 23 April 2012).
IEA 2011, Energy Prices and Taxes, quarterly statistics, 2011 edition, Paris.
International Energy Agency (IEA) 2007a, Energy use in the New Millenium – Trends
in IEA countries, Paris.
Liu, FL and Ang, BW 2003, ‘Eight methods for decomposing the aggregate energyintensity of industry,’ Applied Energy, vol. 76, pp. 15-23.
62
Natural Resources Canada (NRC) 2006, Energy Efficiency Trends in Canada, 1990 to
2004, Office of Energy Efficiency, Ottawa.
Office of Energy Efficiency and Renewable Energy (OEERE) 2005, Energy Intensity
Indicators in the U.S., US Department of Energy.
Pears, AK 2007, ‘Imagining Australia’s energy services futures,’ Futures, vol. 39, pp.
253-271.
Petchey, R. 2010, End use energy intensity in the Australian economy, ABARE–BRS research report 10.08, Canberra, September.
Pitt & Sherry 2012, Energy Efficiency Data Framework: Final Report, prepared for the
Department of Resources, Energy and Tourism, Canberra, April.
Prime Minister’s Task Force on Energy Efficiency 2010, Issues Paper, Department of
Climate Change and Energy Efficiency, Canberra.
Sandu, S and Petchey, R 2009, End use energy intensity in the Australian economy,
ABARE research report 09.17, Canberra, November.
Sandu, S and Syed, A 2008, Trends in Energy Intensity in Australian Industry, ABARE report 08.15, Canberra, December.
Schipper, L, Howarth, RB and Geller, H 1990, ‘United States energy use from 1973 to
1987: the impact of improved efficiency,’ Annual Review of Energy, vol. 15, pp. 455-
504.
Schultz, A and Petchey, R 2011, Energy update 2011, Australian Bureau of
Agricultural and Resource Economics and Sciences, Canberra, June.
Sun, JW 1998, ‘Changes in energy consumption and energy intensity: a complete decomposition model’, Energy Economics (20), pp: 85–100.
63
