Dynamics of technology shifts in the household sector—implications for clean development mechanism

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Energy Policy 34 (2006) 2586–2599 www.elsevier.com/locate/enpol

Dynamics of technology shifts in the household sector—implications for clean development mechanism B. Sudhakara Reddya,, P. Balachandrab a

Indira Gandhi Institute of Development Research, Film City Road, Goregaon (East), Mumbai 400 065, India b Department of Management Studies, Indian Institute of Science, Bangalore 560 012, India Available online 15 September 2004

Abstract The present paper attempts to analyse the dynamics of energy end-use technology shifts in the household sector in India. The technology shifts can be categorized as naturally occurring shifts (with increasing household incomes and availability of energy carriers) and policy-induced shifts (by creating a favourable environment). Initially, the households energy usage patterns, types of energy carriers and the technologies in use are analysed using the data from the National Sample Survey (1999–2000). The energy consumption is disaggregated according to end-use activity and by income groups for rural as well as urban households. It is observed that large variations in energy use exist across different sections of households—urban/rural, low/high-income groups, etc. Further, the paper provides a methodological framework for the diffusion of energy-efficient technologies, and the implications of such diffusions for the Clean Development Mechanism (CDM). It analyses the reasons for the gap between possible and practical implementation of energy-efficient measures, study the reasons for households not using the cost-effective technologies available to them, the benefits of innovation of energy efficiency, and the required policies and specific proposals for government intervention to achieve the potential for the CDM. r 2004 Elsevier Ltd. All rights reserved. Keywords: Household energy; Energy efficiency; Clean development mechanism

1. Introduction One of the most important aspects of the climate change protocol signed at Kyoto in 1997 is the development of an emissions trading mechanism. According to this framework, developed countries can invest in greenhouse gas (GHG) reduction projects in other countries and obtain Certified Emission Reduction (CER) credits. This is referred to as the clean development mechanisms (CDM). Since energy production and utilization contributes more than half of global emissions, it is important to target the energy sector as a GHG reduction strategy. Implementation of this strategy, however, is complicated by two facts. On the one hand, developed countries, though aware of the negative Corresponding author. Tel.: +91-840-0919; fax: +91-22-840-2026.

E-mail address: [email protected] (B.S. Reddy). 0301-4215/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2004.08.019

impacts of climate change, have not changed their high energy-dependent lifestyles. On the other hand, developing countries, which need energy for their economic development, are increasing their energy consumption levels. Under these circumstances, one has to look at ‘‘no regret options’’ which should serve both the purposes, i.e., provide energy services to the consumer and at the same time reduce the negative environmental impacts. Technology and fuel shifts fall into this category. Substituting efficient technologies for inefficient ones and shifting from non-renewable to renewable sources are the ways by which cost-effective services can be provided to the consumers and at the same time reducing negative environmental impacts through decreased energy inputs. Using India’s household sector as a case study, the present paper looks at the prospects of these ‘‘no regret options’’ in the backdrop of CDM.

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The household sector is one of the largest users of energy in India, accounting for about 30 per cent of final energy consumption (excluding energy used for transport). Between 1980 and 2000, the actual amount of energy consumed per household remained almost constant (CMIE, 2001). This static consumption per household has been achieved through improved efficiency. Households that shift to LPG now need 22 per cent less energy for cooking than those using fuelwood. Working against this good news is the increase of activities resulting in rising utilization of energy. Household appliances and automobiles are becoming more efficient, but there are more of them and they are being used more often, even though energy prices have increased at the rate of about 10 per cent per annum. The experience of the last 30 years shows that the rise of gross energy demand has by far exceeded the growth rates of population. The 1990s saw energy use growing at 5 per cent every year, while the Indian population increased by less than 2 per cent. The growth in demand has even offset all the savings achieved by energy efficiency increases within society at large. This highlights the importance of consumption growth as the driving force of energy demand. Given this scenario and the growing share of India in global energy use and CO2 emissions, it is important to analyse the factors that are contributing to this. This paper aims to do so by quantitatively analysing energy requirements of households using a large database on household consumption. More specifically, the main objectives of the paper are to analyse—(i) energy use by different categories of households in India (ii) likely changes in energy consumption over time of different end uses and energy carriers for different categories of households (iii) the underlying social, economic, structural and technical factors that determine changes in household energy use; (iv) impact of technology and fuel shifts, from inefficient to efficient devices and between renewable and nonrenewable sources; and (v) links between household energy use and environment. These objectives are achieved by developing alternate scenarios of future energy use growth and the possible consequences of the implementation of CDM.

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cover the entire fuel cycle, i.e., fuel mining, processing, transporting, conversion, transmission and distribution, and the end use. Only the final end-use service is considered. Fig. 1 shows the methodology adopted here. The framework includes the dynamics of technology shifts from two perspectives (Sudhakara Reddy, 2003). i. Natural technology shifts due to increasing household incomes and availability of modern energy carriers along with influence of market forces. Fuel shifts in households is one of the examples of such phenomena. ii. Policy-induced technology shifts can take place in the households by creating favourable environments through properly designed institutional mechanisms. Shift towards energy-efficient technologies can be achieved through this process. The first step is to conduct a set of technology assessments comparing GHG emissions and economic costs of each energy technology option on a per-unitdelivered-energy basis (Clinch and Healy, 2000). The technologies chosen in the household sector represent realistic alternatives. The next step involves choosing Present Energy Consumption Patterns

Policy Induced Scenario

Future Scenario

Technology Assessment

Technology Replacement

Economic Benefits

Fuel Substitution

Costs

2. Framework for analysis The data collected by the National Sample Survey Organization provide the base for the cross-sectional study for rural as well as urban households (Anon, 2001). The survey deals with (i) social and basic necessities, (ii) consumption by different energy carriers and end uses, and (iii) household expenditure (considered as a proxy for income). The data are disaggregated according to various end-use activities and by expenditure groups. The methodological framework does not

BAU Scenario

Net Benefits

CDM Implementation

Fig. 1. Methodological framework.

Environmental Benefits

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and the corresponding utilizing devices, disposable income of households; availability of fuels and cultural preferences (Reddy A.K.N and Reddy B.S., 1994). Even though price of a fuel plays an important role in the household fuel shifts, it is not possible to study the effect of price in India, where a major part of energy consumption is met by traditional fuels that are gathered informally and the costs consist mostly of time (for gathering fuelwood) and, hence, are opportunity costs. Another reason is that prices of commercial energy carriers such as kerosene are administered and hence do not reflect the real cost. The comparison of energy consumption levels in the urban and rural areas in different income groups for the year 1999–2000 demonstrates various characteristics. An analysis of some of the parameters can help identify the probable scenario in the field of energy consumption in future, and throw light on some of the crucial aspects that are directly linked to sustainability and environment protection (Sudhakara Reddy and Balachandra, 2002, 2003). On the basis of the figures for the year 1999–2000 (Table 1), it can be seen that firewood, which is considered to be inefficiently utilized and hence causes high pollution levels, is being consumed mostly by the low- and middle-income groups in the rural areas and by low-income groups in urban areas because of its easy availability. For example, in the rural regions, nearly 76 per cent of the households use fuelwood out of which nearly 90 per cent belong to the low- and middle-income groups. In contrast, the urban areas have a higher share of LPG consumers, with 44 per cent of total, because of its better distribution network and coverage. The affordability, and accessibility to LPG depends directly on the financial capabilities of the households, which is evident from the lower levels of consumption by the low-income groups in both rural as well as urban areas. Kerosene is the second most important fuel in the urban areas with a significant portion of middle-income

scenarios for GHG reductions. We examine the two most likely policy approaches: energy efficiency improvements and fuel substitution; and two scenarios: Business-as-usual (BAU) and CDM. The BAU scenario accounts for improvements in efficiency and emissions that are expected to occur regardless of GHG control strategies. The CDM scenario maintains the same fuel mix as the BAU scenario, but accelerates the improvement in energy efficiency to achieve significant GHG reductions through various induced policy measures. We examine two pathways, i.e., environmental—leastcost per unit GHG reduction scenario and economic— least-cost per unit reduction scenario. The ‘‘Least cost’’ refers to a pathway in which the cheapest options are taken first until its exhaustion, followed by the next cheapest, etc. These comparisons allow us to examine the relative economic and environmental benefits achieved by different technological and policy approaches to reduce GHG emissions.

3. Results of the study 3.1. Energy use—rural–urban dichotomy Disparities in household energy use exist between rural and urban populations and also between high- and low-income groups. In rural areas, traditional fuels, such as fuelwood, charcoal and agricultural waste, constitute a major portion of total household energy consumption, while in urban areas households use kerosene, electricity and LPG. With increasing disposable income and changes in lifestyles, households tend to move from the cheapest and least convenient fuels (fuelwood and charcoal) to more convenient and expensive ones (kerosene), and finally to the most convenient and usually most expensive types of energy (LPG, and electricity). The main factors that determine the selection of energy carriers include: prices of fuels

Table 1 Percentage share of households using particular energy carrier for cooking/water heating (1999–2000) Region

Income class

Share of households using various energy carriers (%) Firewood

Rural

Low Middle High Total

29.24 39.36 6.95 75.54

(38.71) (52.10) (9.20) (100.00)

Urban

Low Middle High Total

15.24 6.81 0.25 22.29

(68.37) (30.55) (1.12) (100.00)

Kerosene 0.24 1.35 1.12 2.71

(8.86) (49.82) (41.33) (100.00)

7.13 (32.80) 13.11 (60.30) 1.5 (6.90) 21.74 (100.00)

LPG 0.16 (2.96) 2.14 (39.63) 3.1 (57.41) 5.4 (100.00) 5.04 28.16 11.01 44.21

(11.40) (63.70) (24.90) (100.00)

Others

Total

5.84 8.16 2.34 16.35

(35.72) (49.91) (14.31) (100.00)

35.48 51.01 13.51 100

5.35 (45.49) 5.1 (43.37) 1.31 (11.14) 11.76 (100.00)

32.76 53.18 14.07 100

Note: Figures in parentheses represent percentages of households belonging to an expenditure class using a particular fuel.

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households depending on it. Table 1 also demonstrates that other fuels (cow dung, coal, biogas, etc.) appear to be major energy sources in rural areas. The annual per capita energy consumption of lowincome households in urban areas does not differ significantly from that of the rural poor, since the main share of energy consumption in both cases goes to cooking and lighting. However, with rising incomes, the energy consumption patterns of urban households change significantly. This is due to the increase in the number of dishes prepared and the use of various appliances such as TV, microwave, AC, etc. Yet, despite rising income, per capita energy use for cooking remained almost constant over the years because of increased energy efficiency through fuel shifts. The end-use activities serve to focus attention on the degree of household energy utilization. However, they do not illustrate the differences among the energy carriers, consumption and basic demand. Hence, a comparison of average consumption levels across energy carriers and the share of each energy carrier in total demand is necessary. With this in mind, the quantity of fuels used in various income groups for cooking and water-heating is shown in Table 2. From the table, it can be seen that, during the year 1999–2000, the rural population, consisting of 72 per cent of total households, used nearly 90 per cent of fuelwood. Among the rural households, the middle-income group consumes more than 50 per cent of total fuelwood. It is generally perceived that low-income groups are the highest wood consuming groups, but in reality, they consume mainly agricultural wastes, cow dung, etc. However, in urban areas, the low-income households use fuelwood due to the non-availability of agricultural waste, cow dung, etc. In the case of kerosene, the consumption is 5284 million litres, with significant share coming from the middleincome groups. The estimated consumption of LPG is about 5 million tonnes out of which 76 per cent is consumed by the urban population. In the case of lighting, the dominant sources are kerosene and electricity. Kerosene provides lighting to more than 50 per cent of households in the rural areas using mainly wick lamps. These lighting sources have very low levels of energy output. It can be seen from

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Table 3 that the share of households using kerosene for lighting is the highest amongst the low- and middleincome groups in rural areas and low-income groups in urban areas. Electricity is being used by most of the households in urban areas and middle- and high-income groups in rural areas. Table 4 shows that the amount of kerosene consumed for lighting works out to be 4.2 million litres per year. The corresponding figure for electricity is 50,206 GWh. 3.2. Future demand: analysis of energy carrier consumption trends India’s energy consumption is expected to increase at a rate faster than the world average because of its population and the anticipated rapid economic growth. There is a strong positive relationship between growth in per capita income and growth in household demand for commercial energy carriers. As the recent data indicate, the demand for commercial carriers has risen more rapidly than per capita incomes. This reflects the increasing desire for energy services. With increasing disposable incomes and changes in lifestyles, households tend to move from the cheapest and least convenient devices/technologies (biomass-based) to more convenient and expensive ones (kerosene) and finally to the most convenient and expensive types of technologies (LPG and electricity). Urbanization is Table 3 Percentage share of households using particular energy carrier for lighting (1999–2000) Region

Income class

Kerosene

Electricity

Others

Total

Rural

Low Middle High Total

23.97 23.72 2.89 50.58

11.31 26.98 10.14 48.43

0.29 0.49 0.19 0.97

35.6 51.2 13.2 100

Urban

Low Middle High Total

7.64 2.54 0.08 10.26

24.31 50.49 14.34 89.14

0.31 0.28 0.07 0.65

32.3 53.3 14.5 100

38.5

60.6

0.9

100.0

% of total

Table 2 Quantity of fuels used in rural and urban regions by various income groups (cooking and water heating) (1999–2000) Income class

Low Middle High Total % of total

Fuelwood (million tones)

Kerosene (million litres)

LPG (million tones)

Rural

Urban

Total

Rural

Urban

Total

Rural

Urban

Total

77.5 104.1 18.4 200 89.6

16.0 7.1 0.3 23.4 10.4

93.5 111.2 18.6 223.3 100.0

89.4 500.4 415.0 1004.8 19.0

1403.8 2580.8 295.3 4279.9 81.0

1493.2 3081.2 710.3 5284.7 100.0

0.03 0.47 0.68 1.18 23.6

0.44 2.43 0.95 3.82 76.4

0.47 2.9 1.63 5.0

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another important determinant of both the level of energy demand and the type of the energy carrier. With increasing levels of urbanization, the levels of household energy consumption increase although it is difficult to separate the effects of urbanization from the increases in income levels that generally accompany urbanization. Several other factors that contribute to this trend include a decline in access to biomass fuels, inconvenience in transportation and storage, and the availability of commercial carriers in urban areas. Nonetheless, the use of traditional fuels remains significant among low-income groups in many urban centres. The historically observed household energy consumption pattern, current priorities and availability provided the basis for estimating the future demand. The changes in the growth rates of various energy carriers due to the changes in the GDP, population growth rates and urbanization pattern are included. In addition, the natural impact of technological changes and increased access to quality energy are considered for estimating

the future share of households using various energy carriers. Table 5 contains the estimated share of households depending on different energy carriers for cooking. According to the table, by 2010, the share of households using fuelwood will be 64.3 per cent, down from 75.5 per cent during 1999–2000 in rural areas and 10.3 in urban regions (from 22.4 per cent during 1999–2000). The respective increase in LPG shares are 19.2 and 70 per cent. These figures demonstrate not only the increasing urbanization, but also the increasing income levels and affordability to pay for the modern energy-efficient devices. Kerosene is estimated to be used to a certain extent in the low- and middle-income groups in rural as well as urban areas. A gradual rise in the electricity consumption can be seen in the case of urban areas by a rise of 6 per cent share and in case of rural areas 22 per cent. The use of other fuels in urban areas is estimated to drop because of the increasing share of electricity and LPG. As shown in Tables 6 and 7, the demand pattern by energy carriers will change significantly during the next

Table 4 Quantity of energy carriers used in rural and urban regions by various income groups (lighting) Income class

Kerosene (million litres)

Low Middle High Total

Electricity (GWh)

Rural

Urban

Total

Rural

Urban

Total

1.91 1.89 0.23 4.03

0.144 0.048 0.002 0.194

2.054 1.938 0.232 4.224

5249.81 16285.67 5974.61 27510.09

5798.2 11752.93 5145.61 22696.74

11048.01 28038.6 11120.22 50206.83

Table 5 Percentage share of households using particular energy carrier for cooking (2010) Region

Income class

Fuelwood

LPG

Rural

Low Middle High Total

24.89 33.51 5.92 64.31

0.56 7.63 11.04 19.23

Urban

Low Middle High Total

7.02 3.14 0.11 10.27

7.99 44.63 17.45 70.07

Kerosene

Electricity

Others

Total

0.38 2.15 1.78 4.32

0.02 0.22 0.25 0.49

3.43 5.25 1.55 10.23

29.8 49.4 20.81 100.00

4.33 7.97 0.91 13.21

0.20 0.66 0.21 1.08

1.84 1.47 0.08 3.39

22.2 58.7 19.19 100.00

Table 6 Change in energy carrier use from 2000 to 2010 (Rural) Income class

Low income Middle income High income Total

Fuelwood (million tones)

Kerosene (million litres)

Cooking

Water heating

Total

Cooking

Water heating

2.95 3.97 0.71 7.62

0.98 1.32 0.24 2.54

3.93 5.29 0.95 10.16

86.5 484.02 401.4 971.92

29.66 165.95 137.62 333.23

Lighting 0.61 0.61 0.07 1.28

LPG (million tones)

Electricity (GWh)

Total

Cooking

Lighting

115.55 649.36 538.95 1303.87

0.12 1.59 2.3 4.01

4302.2 13346.06 4896.18 22544.44

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Table 7 Change in energy carrier use from 2000 to 2010 (Urban) Income class

Fuelwood (million tones) Cooking

Low income Middle income High income Total

4.33 1.94 0.07 6.34

Water heating 1.44 0.64 0.02 2.11

Kerosene (million litres) Total

Cooking

5.77 2.58 0.09 8.45

164.91 303.19 34.69 502.8

Water heating 56.55 103.95 11.9 172.4

10 years. The consumption of fuelwood would increase by 10 million tonnes in rural areas (a 4 per cent increase since 1999–2000), while there is a significant decline in urban regions by about 8.5 million tonnes (30 per cent decline since 1999–2000). The use of LPG and electricity is estimated to increase in both the urban as well as in rural areas due to their increasing availability. The number of LPG users is estimated to rise significantly because of the dominant middle-income group in the urban areas and high-income groups in the rural areas. However, the use of kerosene is estimated to decline in urban areas while there is a significant increase in rural regions, particularly for cooking purposes. Electricity consumption is likely to reach nearly all the households in urban areas while a switch from kerosene to electricity will be seen in rural regions for purpose of lighting. The expected further growth in electricity consumption for rural lighting will reduce kerosene consumption. With specific reference to the type of energy source used for the activity of water heating, a rapid increase in the use of electricity is estimated in urban areas. Using this information on fuel shifts, the changes in the quantity of energy consumption for various end uses are estimated (Tables 6 and 7). The results in the tables show increase in the quantity of energy used for all end uses such as cooking, water heating and lighting in rural regions except lighting by kerosene. This is due to the fact that with changing life styles and the availability of carriers like kerosene, LPG and electricity, the quantity of energy used will increase. In the case of urban areas one can observe a decline in consumption levels of fuelwood and kerosene for different end uses whereas increases in the levels of LPG and electricity use in all categories of households are expected. This is so because of the shift from fuelwood and kerosene to LPG and electricity use by these households. From Table 8, one could observe the reduction in cooking and water heating needs of urban low-income households. Even in the case of the other two categories of urban households there is a decline in water heating energy consumption. This is mainly due to the adoption of high-quality energy sources, which can be used at higher efficiency levels. Other than this, there is going to be a significant increase in the energy consumption levels of both rural and urban households. The estimated increase (from 2000

Lighting 0.058 0.02 0.001 0.078

LPG (million tones)

Electricity (GWh)

0.52 2.91 1.14 4.57

2799.46 5674.5 2484.39 10958.3

Total 221.52 407.16 46.591 675.28

Table 8 Change in energy consumption (PJ) (2000–2010) Income class

Change for different end uses (PJ) Cooking

WH

Lighting

Total

Rural Low income Middle income High income Total

55.5 152.82 129.97 338.3

16.76 26.98 8.55 52.29

15.46 48.03 17.62 81.11

87.74 227.82 156.15 471.71

Urban Low income Middle income High income Total Grand total % of total

51.29 90.95 49.46 89.11 427.41 76.26

25.05 13.94 0.79 39.79 12.5 2.23

10.07 20.43 8.95 39.44 120.55 21.51

66.27 97.44 57.61 88.78 560.49 100

levels) in consumption, by 2010, is likely to be 472 PJ and 560 PJ, respectively, in the cases of rural and urban households. Rural and urban energy use are combined and total consumption has been estimated. The change in energy consumption from 2000 to 2010 is shown in Table 8. According to the table, there will be a significant increase in rural energy use for cooking among all the income groups. This is due to the possibility of the increase in the use of appliances. In contrast, as noted, there will be a decrease in urban cooking/water heating use. This decrease is due to fuel substitution–from traditional to modern energy carriers which are used more efficiently. The above fact is further illustrated by the figures of changes in per capita energy consumption between 2000 and 2010 (Table 9). Two opposing trends have determined per capita household energy consumption. One is the increase in energy-based life styles due to increases in household income. This trend by itself would have led to a rise in per capita energy consumption. The opposing trend is the more efficient use of energy, through carrier/technology switching (from traditional to modern). Except for low-income households in rural regions, a decline in per capita consumption is seen due to the shift from traditional fuels such as

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Table 9 Changes in per capita consumption (GJ) (2000–2010)

Table 10 Changes in carbon emissions from energy consumption (2000–2010)

Income group

Energy carrier

Quantity

Carbon dioxide % of total emissions (mt)

Fuelwood (mt) Kerosene (million litres) Electricity (from coal ) (GWh) LPG (mt) Others (mt)

1.71 628.6

11.12 1.24

62.5 7.0

7670

5.4

30.4

0.012 17.8

0.1 100.0

End use Cooking

Water heating

Lighting

Average

Low income Middle income High income Average

0.43 1.22 3.24 1.5

0.1 0.69 1.83 0.84

0.31 0.45 0.05 0.35

0.84 1.46 5.11 1.99

Low income Middle income High income Average

2.23 1.13 0.09 1.78

1.26 0.97 0.29 1.24

0.71 0.05 0.55 0.11

2.78 2.16 0.74 2.92

fuelwood to modern carriers like LPG and electricity. Since this shift may not take place in a majority of the low-income rural households, the per capita consumption in this group will not show the declining trend. All in all, however, the overall share of household spending on energy generally decreases, even when it grew in absolute terms with increasing income. 3.3. Environmental impacts of energy consumption Production and consumption of almost any type of energy have environmental impact. Harvesting of fuelwood, in particular, contributes to deforestation, soil erosion, and desertification. Use of fuelwood as an energy source in an unsustainable manner can contribute to the accumulation of CO2 emissions, the main GHG, both because burning fuelwood produces CO2, and because deforestation destroys an important CO2 sink. In addition, the use of biomass in traditional stoves exposes the users, mainly women and children, to high levels of indoor air pollution. The prevalent use of coal for electricity generation, with little emission controls, is contributing significantly to the degradation of air quality and increasing GHG emission levels. Since the environmental implications are significantly dependent on the type of energy carrier chosen, we have estimated the carbon emissions through various carriers. Table 10 shows the changes in CO2 emissions due to fuel and technological shifts. According to the table, the total CO2 emissions will decline by 17.8 million tonnes in the residential sector of which two-thirds comes from fuelwood. Thus, technological improvements and changes in the fuel-mix are therefore of great significance to environmental considerations. 3.4. The economics of energy efficiency Here, we analyse the economic feasibility of all the technological alternatives in terms of their costs and benefits. This will allow us to compare the returns from traditional technologies/fuels with efficient technologies/

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fuels. For example, if a standard technology for cooking activity is replaced by an efficient one, the energy/ family/year will be saved to the tune of 50–300 per cent depending on the type of technology that is being replaced. A reduction in energy consumption will automatically translate into reduction in GHG emissions. Moreover, a tonne of emissions averted in the household sector will generally cause a greater reduction in human exposure than a tonne of outdoor emissions averted in the industrial sector. However, this comes at a considerable economic cost. To estimate the long-term economic and environmental benefits, it is necessary to link each specific technological option to a particular GHG reduction scenario with the accompanying costs. The use of efficient devices demonstrates the advantages of climatic benefits in terms of reducing the emission levels as well as the incremental costs. Thus, the cost and benefits of reducing a tonne of emissions in technological shifts (from inefficient to efficient) might be more than a tonne of emissions averted while shifting from one fuel to another (kerosene to LPG). To estimate these we resort to conduct a set of technology assessments, comparing emissions and economic costs of each technology option on a per-unit-deliveredenergy basis. The technologies chosen represent the realistic alternatives that are available in India. Table 11 provides the results of comparative analysis of economic costs and carbon emission levels of the chosen technology alternatives. The analysis assumes a family size of five people per household. In the case of lighting, the possible alternatives are incandescent bulbs (IB), fluorescent tubes (FT) and compact fluorescent lamps (CFL). In a typical house, lighting will be required at various locations with different intensity levels (lumens) and varying usage hours per day. In such situations, replacing a device with an efficient one may not provide an optimal solution. Depending on the location, hours of usage and the lumens required, the lighting devices also may change. Considering this, alternative packages of lighting consisting of required number of IBs, FTs and CFLs are developed (Table 11).

25 250 125 250

25 250 125 250

49 816 494 1268 717 1506 1506 1921

Water heating Traditional wood stoves (13%) Efficient wood stoves (35%) Traditional kerosene stoves (30%) Efficient kerosene stoves (45%)

Lighting Standard package—I Efficient package—I Standard package—II Efficient package—II Standard package—III Efficient package—III Standard package—IV Efficient package—IV 350.4 73.7 455.5 172.3 444.6 158.6 685.5 260.8

500 210 96 58

1500 500 280 186

kWhs kWhs kWhs kWhs kWhs kWhs kWhs kWhs

kgs kgs Litres Litres

kgs kgs Litres Litres

Capital cost Energy Units (Rs.) (per family/year)

Cooking Traditional wood stoves (13%) Efficient wood stoves (35%) Traditional kerosene stoves (30%) Efficient kerosene Stoves (45%)

Options (with efficiencies)

Table 11 Details of standard and efficient energy using devices

1.261 0.265 1.640 0.620 1.600 0.571 2.468 0.939

8 3.36 3.36 2.03

24 8 9.8 6.51

3 3 3 3 3 3 3 3

1 1 8.5 8.5

1 1 8.5 8.5

1051.2 221.2 1366.6 516.8 1333.7 475.8 2056.4 782.4

500 210 816 493

1500 500 2380 1581

65.2 151.8 149.6 242.3 203.9 303.0 273.4 389.7

6.6 40.7 25.7 40.7

6.6 40.7 25.7 40.7

1116.4 373.0 1516.2 759.2 1537.6 778.8 2329.9 1172.1

506.6 250.7 841.7 533.7

1506.6 540.7 2405.7 1621.7

0.6972 0.6972 0.6972 0.6972 0.6972 0.6972 0.6972 0.6972

105 105 70.43 70.43

105 105 70.43 70.43

kg/kWh kg/kWh kg/kWh kg/kWh kg/kWh kg/kWh kg/kWh kg/kWh

kg/GJ kg/GJ kg/GJ kg/GJ

kg/GJ kg/GJ kg/GJ kg/GJ

Energy Energy price Energy cost/ Annualized capital Total annual CO2 emissions/ Units unit energy (GJ) (Rs/unit) year (Rs.) cost (Rs./year) cost (Rs.)

244.30 51.40 317.59 120.11 309.95 110.57 477.91 181.82

840.00 352.80 236.64 142.97

2520.00 840.00 690.21 458.50

Total CO2 emissions (kg)

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The estimates of cost and carbon emission (indirect emissions due to the use of electricity generated mainly using coal) levels are made for these alternative packages rather than individual devices. Observing the information provided in Table 11, one can state that the use of efficient devices promises environment friendly solutions in terms of reducing the total carbon content as a result of the reduced emissions. For cooking, as the table shows, replacing a traditional wood stove with an efficient one results in maximum reduction of CO2 emissions. In the case of the cooking and water heating activity it is the efficient wood stoves that dominate, while lighting, an efficient package is the best alternative.

4. Future scenario—a win–win solution through CDM We examine the two scenarios of energy efficiency and fuel substitution (least-cost per unit GHG reduction). The energy efficiency scenario maintains the same fuel mix as the BAU scenario but accelerates the demand side energy efficiency to reduce GHG emissions. The fuel substitution scenario is intended to explore the pathway of fuel switching from traditional to modern energy carriers to reduce GHG emissions while keeping the end-use efficiency of each fuel-using technology constant. A comparison of these pathways allows us to examine the relative economic and environmental net benefits achieved by different technological and policy approaches to reduce GHG emissions. From Table 12, it can be seen that the use of efficient devices helps save a considerable amount of energy, as against the traditional fuel sources, especially in urban areas. In the case of cooking activity, middle-income groups are estimated to save a higher quantity of energy, followed by high-income groups in rural areas and middle-income groups in rural areas by using kerosene. In the case of lighting in urban areas, middle-income groups are estimated to save more energy if replaced by

efficient devices, followed by middle-income groups and high-income groups in rural areas. It can be seen that in rural areas, replacing existing traditional lighting devices with efficient ones (as a package) results in considerable amount of energy savings. For example, for the year 2010–2011 a saving of 64 GWh per household can be achieved. Therefore, the need to focus in the rural areas for generating awareness for using energy-efficient devices is crucial especially in the middle-income groups. Another feature with the use of energy-efficient devices is that the higher the investment cost, the higher will be the benefits of energy savings and the higher the annual cost savings (Table 13). Besides the various monetary benefits, the use of energy-efficient devices also demonstrates climatological benefits. A higher investment at the initial stage is useful in the long-term because of higher savings in annual costs and energy. Table 14 presents the estimated GHG abatement potential of different alternatives and their cost implications. Replacing the traditional wood stoves with efficient ones results in the highest potential for CO2 emission reduction. All the alternatives of shifting to efficient devices have negative incremental cost of abatement. This is significant because it means that no alternative needs any net additional cost to adopt efficient devices. Cost savings obtained due to the energy savings more than compensate for the additional cost. Rather than any outflow, the adopter is going to benefit significantly from this shift.

5. Energy efficiency projects for CDM—potential available Higher rates of diffusion of energy-efficient technologies (both for renewable and non-renewable energy) in the household sector need the mechanism of a powerful catalyst. The CDM is one such mechanism and, if implemented, can effectively speed up the process of technology diffusion. The CDM is a market-based

Table 12 Energy savings due to using efficient devices in 2010–11 Options

Low income

Middle income

High income

Total

Total (PJ)

Cooking/water heating—rural Firewood (million tonnes) Kerosene (million litres)

10.70 20.98

21.02 184.48

6.22 231.65

37.95 437.11

607.12 15.30

Cooking/water heating—urban Firewood (million tonnes) Kerosene (million litres)

1.34 105.00

0.87 380.34

0.05 70.12

2.27 555.46

36.24 19.44

Lighting: rural Electricity (GWh)

1537.28

5478.46

3485.40

10501.14

37.80

Lighting: urban Electricity (GWh)

1589.58

5587.60

3316.19

10493.37

37.78

Lighting Standard package—I by efficient package—I Standard package—II by efficient package—II Standard package—III by efficient package—III Standard package—IV by efficient package—IV

Water heating Traditional wood stoves (13%) by efficient wood stoves (35%) Traditional kerosene stoves (30%) by efficient kerosene stoves (45%)

Cooking Traditional wood stoves (13%) by efficient wood stoves (35%) Traditional kerosene stoves (30%) by efficient kerosene stoves (45%)

Substitution alternatives (with efficiencies)

743.5 757.0 758.8 1157.7

1268

1506

1921

308.0

250

816

255.9

784.0

250

250

965.9

49.69

49.35

49.93

66.59

36.59

50.52

32.59

64.11

Cost savings (Rs.) Annual rate of returns (%)

250

Investment (Rs.)

Table 13 Monetary benefits of substituting standard devices with efficient energy using devices

60.27

50.38

59.70

91.11

123.2

102.4

313.6

386.4

ROI (%)

1.66

1.98

1.67

1.10

0.81

0.98

0.32

0.26

Payback period (years)

116.3

99.1

92.7

86.6

15.0

34.1

15.0

34.1

Incremental cost (Rs.)

1.53

1.03

1.02

1.00

1.3

4.6

3.3

16.0

Energy saved (GJ)

76.06

96.29

90.89

86.90

11.29

7.35

4.56

2.13

Unit cost of energy saved (Rs./ GJ)

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Lighting Standard package—I by efficient package—I Standard package—II by efficient package—II Standard package—III by efficient package—III Standard package—IV by efficient package—IV

Water heating Traditional wood stoves (13%) by efficient wood stoves (35%) Traditional kerosene stoves (30%) by efficient kerosene stoves (45%) 743.5 757.0 758.8 1157.7

197.5

199.4

296.1

308.0

93.7

192.9

255.9

784.0

231.7

487.2

965.9

Total (Rs.)

Incremental cost

1680.0

CO2 emission abated (kg)

3910.17

3805.72

3.81 3.91

3833.64

3854.22

3287.96

525.264

3383.43

574.946

Tonne of CO2 abatement (Rs./t of CO2)

3.83

3.85

3.29

0.53

3.38

0.57

CO2 abatement (Rs./ kg of CO2)

14337.3

13954.3

14056.7

14132.1

12055.8

1926.0

12405.9

2108.1

Tonne of Carbon abatement (Rs./t C)

81.46

79.29

79.87

80.30

68.50

10.94

70.49

11.98

Tonne of CO2 abatement (US$/t of CO2)

298.69

290.71

292.85

294.42

251.16

40.12

258.46

43.92

Tonne of carbon abatement (US$/t C)

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Cooking Traditional wood stoves (13%) by efficient wood stoves (35%) Traditional kerosene stoves (30%) by efficient kerosene stoves (45%)

Substitution alternatives (with efficiencies)

Table 14 GHG abatement benefits of substituting standard devices with efficient energy using devices

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mechanism that was introduced under the Kyoto Protocol to the United Nations Framework Convention on Climate Change. CDM is expected to transform the environmental issues from an unwanted externality into an attractive business opportunity for the industry/ entrepreneurs. An entrepreneur can expect to generate revenue through both selling the direct outputs (energy produced from renewable energy projects) and by CERs generated through carbon emission reductions. Energy efficiency in the household sector, with its huge potential (Table 15) throws up lots of new opportunities for CDM projects. It may be observed from the table that the estimated ultimate potential in terms of number of households that could be induced to use efficient devices runs into millions. The total annual energy savings by 2010–11 is expected to be about 753 PJ, while the corresponding GHG reduction potential is 84 million tonnes. Even in terms of incremental abatement costs, these alternatives seem to be very attractive. All of them have negative incremental costs, i.e., no net monetary outflows while adopting efficient devices. Rather, the households are likely to reap significant benefits due to the saved energy. Any benefits accruing through the sale of carbon credits under CDM will be entirely additional. This may make the energy efficiency projects in the household sector more attractive for implementation under CDM. However, the exploitation of its full potential may not be possible since all the households may not be willing to adopt efficient devices. Even then, it may be possible to initiate a large number of projects, which are amenable to CDM guidelines, with an effective implementation mechanism. Energy efficiency projects tend to have peculiarities that need to be taken into account when developing such projects. In contrast to other sectors, energy efficiency

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projects often comprise bundles of smaller projects. Energy efficiency projects are more likely to be characterized by two factors:

 

They span a large number of sites or locations. There is a specified target market area, although multiple sites may be targeted.

The energy efficiency projects in the household sector tend to be small and individually may not become attractive propositions as CDM projects. International private agencies may neither be willing to invest in these small-scale projects nor show any interest in buying CERs. It is essential to pool these small-scale projects into a large project under a single entity. An intermediary like Energy Service Company (ESCO) can play an important role towards this. An ESCO can involve itself in implementing large number of energy efficiency projects and pool together the CERs obtained through energy savings for international buyers. The risks associated with accepting an ‘‘incorrect’’ project varies significantly based on the type of energy efficiency project. The potential negative outcomes of using an ‘‘incorrect’’ pre-project estimate (baseline) is probably the highest if an energy efficiency project includes only one or two very large facilities (e.g., district heating systems, large industrial applications). Projects that embody a portfolio concept, where several energy efficiency measures are installed across a large number of sites, may pose less risk (as the baseline would probably be ‘‘correct’’ for the project as a whole, even though some individual components may not conform to it and be ‘‘additional’’ on their own). Thus developing a CDM project based on energy efficiency in the household sector needs participation of multiple stakeholders.

Table 15 Estimated potential for energy efficiency of CDM projects in the households sector by 2010–11 No. of households (million)

Annual energy savings potential (PJ)

Annual CO2 emission abatement potential (million tonne)

Cooking/water heating—rural Efficient wood stoves Efficient kerosene stoves

29.41 3.31

607.12 15.30

63.75 1.08

563.78 3355.94

Cooking/water heating—urban Efficient wood stoves Efficient kerosene stoves

1.76 4.21

36.24 19.44

3.81 1.37

563.78 3355.94

37.09

37.80

7.32

3827.38

32.96

37.78 753.68

7.32 84.65

3842.96

Options

Lighting: rural Efficient packages Lighting: urban Efficient packages Grand total

Incremental cost of CO2 abatement (Rs./t of CO2)

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6. Implementation mechanism Energy efficiency and technology management play an important role in economic development, family health and environmental conservation. This means that improvements in energy utilization and efforts to disseminate new technologies offer not only opportunities to climb the energy ladder, but also opportunities for positive social change. Hence, it is important for the government and other organizations to intervene and promote new, efficient technologies. However, it is equally important that market forces and commercial strategies are the final test for the viability of a technology project. There is no reason to believe that energy efficiency projects will not succeed in the market when they are implemented through innovative methods and local stakeholder involvement. To achieve this goal, funding agencies must encourage the financing of efficiency programmes in order to develop a strong indigenous resource base and experience. Importantly ‘‘think locally can aggregate into acting globally,’’ and local entrepreneurs should be encouraged so that local knowledge and control of projects can be taken care of. The provision of financial and infrastructure resources that can be managed by households and poor communities have to be increased. This approach, however, requires capacity building in education and training. The first step in this direction for the government or any other organization could be to provide small-scale decentralized funding to groups of women, households, or communities to experiment with, and evaluate, a range of energy technologies, including improved cook stoves, solar devices and biogas technologies. These technology resource centres can operate under the management of local entrepreneurs who could provide wide-ranging technical expertise to local people. This approach of designing rural energy technology centres provide a broad selection of technical resources to the consumers and ensure that end users can choose what works for them. This will also eliminate the famous ‘‘subsidy schemes’’, which were based on laboratory experiments and were designed in a grand scheme somewhere else. An important goal for future programmes will be to integrate the nurturing, capacitybuilding features of technology efforts with market reach and benefits of scale that can be achieved in programmes that stimulate commercial interest in smallscale and household energy technologies. The impact of CDM on the issue of sustainable development in developing countries is by far the most important issue that arises from the energy demand and supply discussion. The real impact of the CDM lies in its potential to increase efficiency through private investment. Through the CDM route, significant investments in the energy sector with choices of renewable as well as

efficient technologies and practices can be brought in. Purely from a financial point of view, the CDM represents a clear way to reduce environmental degradation by providing private capital markets with the means to invest in carbon reductions. It will also provide an unprecedented business opportunity for developing countries like India, which is at a critical juncture in its economic development. Hence, a proper mechanism, which aims at forcing the market forces to act in favour of energy efficiency is the need of the hour.

7. Conclusions The comparison of values of energy consumption in urban and rural households for the year 1999–2000 and estimated values for the year 2010–2011 demonstrate various characteristics. An analysis of some of the parameters helped us to develop a probable scenario of household energy consumption in the future, and throws light on some of the crucial aspects directly linked to sustainability and environmental protection. After analysing the cost-effective GHG mitigation options and assessing their environmental benefits, we have examined the costs and benefits of shift from conventional and inefficient technologies to efficient ones, both in the case of non-renewable fuel sources and renewable ones (e.g., efficient wood stoves). Then, we estimated the marginal net economic costs of GHG reduction, which are the differences between these two. We discussed the data in the light of typical household size, technology, and consumption behaviour. The results corroborated the significance of consumption behaviour. On the one hand, behavioural changes can lead to substantial energy savings; these may even be higher than the savings achieved by persistent technological progress. On the other hand, however, an opposite development path is possible, too: if consumption growth exceeds the rate of energy efficiency gains, overall energy demand is likely to rise. The present study finds that GHG emission reductions resulting from changes in energy use can be accompanied by substantial short-term economic benefits. However, the degree of these benefits varies with the choice of energy technologies and carriers. According to this study, shifting from inefficient to efficient technologies, e.g., results in greater reduction of emissions than the shifting between renewable and non-renewable fuels, though this cannot be generalized. Hence it can be safely concluded that economic benefits alone seem to be large enough to offset the incremental economic costs associated with introducing GHG reduction strategies. This indicates that these strategies can truly be referred to as ‘‘no-regrets options’’. If we include secondary benefits such as energy security, employment creation, technology transfer, and ecosystem disruption, then the

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volume would be much higher. Such near-term secondary benefits of GHG control provide the opportunity for a true no-regrets environmental policy in which substantial advantages accrue even if the impact of humaninduced climate change turns out to be less than many people now fear. These results have important implications for emissions trading in the form of CDM. The near-term health improvements are local, i.e., they cater entirely to the nation in which CDM projects are undertaken. This is unlike the benefits of GHG reductions, which accrue globally. Such large local benefits may provide a significant extra incentive for India to enter into arrangements by which local GHG controls are financed externally and the CERs are shared. Indeed, this study shows that a GHG reduction global strategy can actually be consistent with national development objectives, such as increasing energy efficiency, reducing local air pollution levels, and improving social equity by providing energy services to remote rural areas through renewable energy sources. Sharing GHG reduction credits in return for local

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benefits would obviously be more attractive to developing countries if it involved access to financial flows otherwise not available to them.

References Anon, 2001. Results of the National Sample Survey Organisation for the Household Sector. NSSO, Government of India, New Delhi. Clinch, J.P., Healy, J.D., 2000. Cost benefit analysis of domestic energy efficiency. Energy Policy 29(1). CMIE, 2001. India’s Energy Sector. Centre for Monitoring Indian Economy, New Delhi. Reddy, A.K.N., Reddy, B.S., 1994. Substitution of energy carriers for cooking in Bangalore. Energy—The International Journal 19 (5), 561–572. Sudhakara Reddy, B., 2003. Overcoming the energy efficiency gap in India’s residential sector. Energy Policy 31(11). Sudhakara Reddy, B., Balachandra, P., 2002. Sustainable energy planning for India revisited. Economic and Political Weekly XXXVII(52), December 28. Sudhakara Reddy, B., Balachandra, P., 2003. Integrated energyenvironment-policy analysis. Utilities Policy 11, 59–73.