Advanced Materials Research Vol. 689 (2013) pp 54-59 © (2013) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMR.689.54
Life Cycle Energy and CO2 Emissions of Residential Buildings in Bandung, Indonesia Usep Surahman1,a, Tetsu Kubota1,b 1
Graduate School for International Development and Cooperation, Hiroshima University, 1-5-1 Kagamiyama, Higashi Hiroshima, Hiroshima 739-8529, Japan a
b
[email protected],
[email protected]
Keywords: Life cycle assessment, Energy consumption, CO2 emissions, Input-output analysis, Indonesia.
Abstract. This study aims to develop a simplified life cycle assessment model for residential buildings in Indonesia, which can be used under relatively poor data availability conditions. In order to obtain material inventory data and household energy consumption profiles for constructing the above model, a survey was conducted in Bandung in 2011. This paper analyzes life cycle energy and CO2 emissions employing an input-output analysis-based method within unplanned houses (n=250), which are classified into three categories, namely simple, medium and luxurious houses. The results showed that the average embodied energy of simple, medium and luxurious houses was 36.3, 130.0 and 367.7 GJ respectively. The cement consumed the largest energy and emitted the most CO2 emissions among all materials. The annual average operational energy of simple, medium and luxurious houses varied widely at 11.6, 17.4 and 32.1 GJ/year respectively. The energy consumption for cooking accounted for the largest percentage of operational energy. The profiles of life cycle CO2 emissions were similar with those of life cycle energy. The factors affecting embodied, operational and life cycle energy were also studied. Introduction Life cycle assessment (LCA) of energy and CO2 emissions for buildings is a strong analytical tool to find out design alternatives to achieve a more sustainable building. In fact, several LCA methods for buildings were developed and are commonly used in many parts of the world, particularly in developed nations. However, there are relatively few LCA studies for buildings in developing countries such as in Indonesia to date. This is mainly because of relatively poor availability of building, economic and environmental data. This study aims to develop a simplified LCA model for residential buildings in major cities of Indonesia, which can be used under these circumstances. A survey was conducted in the city of Bandung, Indonesia from September to October 2011, in order to assemble the necessary data for constructing the above model. This paper analyzes life cycle energy and CO2 emissions within unplanned houses in the city, employing an input-output (I-O) analysis-based method. The factors affecting embodied, operational, and life cycle energy are also discussed. Methodology Case Study Houses. Bandung city, which was selected as case study city, is located on 791 m above the sea level having humid and relatively cool climate. This study focuses on unplanned houses because in most of the major cities in Indonesia, unplanned houses account for the largest proportion of the existing housing stocks, which is about 89% in case of Bandung [1]. These houses can be classified into three categories based on construction cost and lot area (Fig. 1.), namely simple, medium and luxurious houses, having the average approximate life span of 20, 35 and 50 years respectively [2]. A total of 250 unplanned houses were investigated in the survey (Table. 1.). As shown, the averaged total floor area of simple houses was 57 m2, while that of medium houses was All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of TTP, www.ttp.net. (ID: 133.41.91.138-12/03/13,02:54:16)
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127 m2. Luxurious houses had larger area of 300 m2. The major building materials used were found to be almost the same among the above three categories, though a slight difference can be seen in terms of materials for floor and roof. (b)
(a)
(c)
Figure.1. Case study houses; (a) simple house; (b) medium house; (c) luxurious house. Table.1. Size and major materials of case study houses House category
Sample size
Average floor/lot area (m2)
Structure
Foundation
Building materials Floor
Walls
Roof
Simple houses Medium houses Luxurious houses
120 100 30
57/49 127/122 300/480
Concrete Concrete Concrete
Stone Stone and concrete Stone and concrete
Cement Ceramic tile Ceramic and granite tile
Clay brick Clay brick Clay brick
Clay tile Clay tile Concrete tile
Total
250
Table.2. Profile of respondents House category
Major ethnic group
Simple houses Medium houses Luxurious houses
Sundanese (90%) Sundanese (77%) Sundanese (53%)
Average household size (person(s)) 4.7 4.9 5.5
Average monthly income (USD) 222 - 333 444 - 555 556 - 1111
Table.3. Data sources and collection methods Phase
Data
Source
Collection methods
Material production
Material inventory
Design record
Operation
Household energy consumption
Usage of appliances Utility bills
House owner interview On-site building measurement House owner interview On-site measurement
A brief profile of respondents is shown in Table. 2. The average household size of the sample was 4.7 persons in simple houses, 4.9 persons in medium houses and 5.5 persons in luxurious houses. The average monthly household income was also investigated by a multiple-choice question. As expected, the households in luxurious houses have higher monthly incomes than the others. Life Cycle Assessment (LCA). LCA generally involves six phases, namely design, material production, construction, operation, maintenance and demolition phases. However, design, construction and demolition phases are not considered in this paper. This is because most of the housing stocks in Bandung are not designed in formal way but constructed and demolished by manual labor. Thus the energy consumption and materials used during the above phases are considered negligible. Data sources and collection methods used in respective phases of the present survey are shown in Table. 3. The design records such as building drawing are required for the analysis of embodied energy. These data can normally be obtained from the local authorities, developers, consultants, contractors or architects [3-5]. Nevertheless, these data were only available for a few medium houses and most of the luxurious houses in Bandung. On the other hand, most of the simple and medium houses are constructed not in the formal way in practice and therefore the inventory record cannot be obtained. Thus, for simple and medium houses, the actual on-site building measurements were conducted instead in order to acquire the data (Fig. 2a.). The detailed household energy consumption data are necessary for the analysis of operation phase. Few previous investigations on the household energy consumption were carried out in Indonesia [3, 4] by interviewing the house owners and measuring the energy consumption on-site. Since the energy consumption data record is not available in Bandung, the detailed interview was conducted to obtain the data (Fig. 2b.). These data collections were time consuming and costly. Therefore, simplified projection methods are strongly needed to acquire the necessary data for LCA. This study uses I-O analysis-based method to calculate embodied energy and estimate its CO2 emissions. This is because this method is considered the most appropriate and effective under
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Initial embodied energy (GJ)
(a)
Initial embodied energy (GJ)
relatively poor data availability conditions such as in Indonesia compared with two other LCA methods, namely process-based and hybrid-based methods [6]. The latest Indonesian nationwide I-O table published in 2005 [7] consisting of 175 x 175 sectors was used for calculating the embodied energy and CO2 emissions. The detailed procedure of the embodied energy and household energy consumption calculation are described in the previous paper [8]. 400 (b)
Clear glass Paint Gypsum Clay tile Wood Clay brick Stone Foundation Concrete Sand Ceramic tile Steel Cement
350 300 250
200 150
100 50 0
Figure.2. On-site measurement; (a) Building material survey; (b) Household energy consumption survey
Simple house
Medium house
Luxurious house
Figure.3. Initial embodied energy of each house
Results and Discussion Embodied Energy. The initial embodied energy was calculated for respective houses through previously explained I-O analysis-based method. As indicated in Fig. 3., the cement gives the largest percentage in all the houses (41-42%) followed by the steel (12-16%), the ceramic tile (8-14%) and the sand (7-11%), etc. Both cement and steel did not account for a large volume percentage, but their embodied energy was found to be large. This is simply because the embodied energy conversion factors for these two materials are high. As shown, the estimated embodied energy was 36.3, 130.0 and 367.7 GJ for simple, medium and luxurious houses respectively. Since there is no reliable life-span prediction of building materials in Indonesia, the embodied energy for maintenance is not considered in this study. The correlation analysis was conducted to explain the embodied energy as shown in Table. 4. Several significant variables with relatively higher r-value were selected from Table. 4. and multiple regression analyses were carried out in three house categories (Table. 5.). Table.4. Correlation coefficient between selected variables and embodied energy of each house Simple houses Variables 1 2 3 4 5 6 7
Total floor area Household income Lot area Duration of living Household size Building age House’s storey
Medium houses
r-value
Sig.
0.84 0.77 0.44 0.13 0.12 0.09 0.07
** ** ** -
Variables
Luxurious houses
r-value
Sig.
0.90 0.80 0.50 0.30 0.22 0.15 0.12
** ** ** ** * -
Total floor area Household income House’s storey Household size Lot area Duration of living House location
Variables
r-value
Sig.
0.97 0.82 0.47 0.31 0.29 0.17 -0.10
** ** ** * -
Total floor area Household income Building age Household size Duration of living Lot area House’s storey
* = Significant at 5% level; ** = Significant at 1% level
Table.5. Coefficient of variables included in regression equation for each house (embodied energy) Simple houses Variables 1 2 3
Unstandardized
Standardized
coefficient
coefficient
Total floor area 0.31 0.59 Household income 0.03 0.36 House’s storey Constant 10.54 R2 0.77 * = Significant at 5% level; ** = Significant at 1% level
Medium houses Sig. ** ** -
Unstandardized
Standardized
coefficient
coefficient
0.53 0.52 20.49 -1.89 0.89
0.65 0.26 0.19
Luxurious houses Sig. ** ** **
Unstandardized
Standardized
coefficient
coefficient
1.06 0.53 -10.46 0.95
0.84 0.16 -
Sig. ** ** -
As indicated in Table. 5., the standardized coefficient is the highest in ‘total floor area’ at 1% significant level for all houses, followed by ‘household income’ for simple and luxurious houses, and
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2500
35
Personal Gadgets Cooling Washing Entertainment Lighting Cooking
30 25 20
(GJ) Operational energy (GJ) Operational energy
(GJ/year) Energy Energy consumption (GJ/year) consumption
‘house’s storey’ for medium houses. This indicates that the above variables, especially ‘total floor area’ and ‘household income’, can explain the embodied energy. In the regression equations, the coefficient of determination (R2) is 0.77 for simple houses, 0.89 for medium houses, and 0.95 for luxurious houses respectively, which indicate that 75-95% of the spatial variation of embodied energy can be explained by the above variables.
15 10
2000
Kerosene
Gas 1500
Electricity
1000
500
5
0
0 Simple house
Medium house
Simple house
Luxurious house
Figure.4. Annual mean energy consumption of each house
Medium house
Luxurious house
Figure.5. Operational energy of each house Each vertical bar represents standard deviations for the respective mean values.
Operational Energy. The annual mean energy consumption including electricity, gas, and kerosene was calculated based on the survey data (Fig. 4.) and varied widely at 11.6, 17.4, and 32.1 GJ/year for simple, medium and luxurious houses respectively. It was found that the cooking accounts for the largest percentage for all house categories (45-79%), followed by the lighting (9-27%), the entertainment (8-13%) and the washing/bathing (4-9%). The cooling accounts for the small percentage (1-5%). This is because Bandung experiences relatively cool climate as explained before. The operational energy of the houses during their building life-spans was estimated (Fig. 5.). As shown, the gas and the electricity dominate the operational energy for simple and medium houses. On the other hand, the percentage of electricity shows higher percentage (68%) than that of gas for luxurious houses. This is because the lighting contributes more energy (27%) for luxurious houses due to their large building sizes. The average operational energy for simple, medium and luxurious houses was 233.1, 607.7, and 1603.1 GJ respectively. Table.6. Correlation coefficient between selected variables and operational energy of each house Simple houses Variables 1 2 3 4 5 6 7 8 9
Total floor area Household income Refilling cooking gas Lot area Number of TV Household size Duration of living House’s storey Building age
Medium houses
r-value
Sig.
0.86 0.81 0.76 0.42 0.18 0.17 0.14 0.08 0.07
** ** ** ** * * -
Variables
Luxurious houses
r-value
Sig.
0.88 0.85 0.49 0.47 0.37 0.28 0.26 0.23 0.18
** ** ** ** ** ** ** ** *
Total floor area Household income House’s storey Number of TV Refilling cooking gas Lot area Household size Duration of living Building age
Variables
r-value
Sig.
0.90 0.78 0.54 0.52 0.33 0.30 0.20 0.17 0.13
** ** ** * -
Total floor area Household income Building age Number of AC Duration of living Refilling cooking gas Number of TV Household size Lot area
* = Significant at 5% level; ** = Significant at 1% level
Table.7. Coefficient of variables included in regression equation for each house (operational energy) Simple house Variables 1 2 3 4 5
Unstandardized
Standardized
coefficient
coefficient
Total floor area 1.29 0.49 Household income 0.11 0.28 Refilling cooking gas 4.27 0.27 House’s storey Lot area Constant 75.00 R2 0.86 * = Significant at 5% level; ** = Significant at 1% level
Medium houses Sig. ** ** ** -
Unstandardized
Standardized
coefficient
coefficient
1.69 0.36 77.03 0.10 0.77 0.89
0.49 0.42 0.17 0.09
Luxurious houses Sig. ** ** ** *
Unstandardized
Standardized
coefficient
coefficient
4.28 318.74 0.82
0.91 -
Sig. ** -
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As before, the correlation analysis was attempted to examine the determinants of the above operational energy in respective houses as shown in Table. 6. Several variables recorded high r-values. Multiple regression analyses were carried out by using the above selected variables in three house categories. Table. 7. indicates the coefficient of all variables included in the regression equations in respective houses. As indicated in Table. 7., the standardized coefficient is the highest in ‘total floor area’ at 1% significant level for all categories, followed by ‘household income’ and ‘refilling cooking gas’ for simple houses, while ‘household income’, ‘house’s storey’ and ‘lot area’ for medium houses. This indicates that the above variables are considered to be good predictors to the household operational energy. Life Cycle Energy. The life cycle energy for respective houses was obtained by combining embodied energy and operational energy for respective houses (Fig. 6.). As shown, the operational energy tends to be greater than embodied energy for respective houses by 4 to 7 times. Similar correlation analysis was attempted as indicated in Table. 8. As shown, several variables show strong relationships with the life cycle energy. This result is almost the same as that of operational energy (see Table. 7.). As before, multiple regression analyses were carried out by using the above selected variables in three houses. As indicated in Table. 9., the selected variables which have the highest standardized coefficient are the same as those of operational energy. This is simply because the operational energy accounts for the largest portion in their life cycle energy. 450
(tons CO2 -eq) COCO2 emissions (toone-C/years) 2 emissions
energy cycleenergy Life (GJ) (GJ/years) Life cycle
3500 3000 2500
Operational energy
2000
Embodied energy
1500 1000 500 0 Simple house
Medium house
400 350
300
Operational CO2 emissions
250
Embodied CO2 emissions
200 150 100 50 0
Luxurious house
Simple house
Medium house
Luxurious house
Figure.6. Life cycle energy of each house.
Figure.7. Life cycle CO2 emissions
Each vertical bar represents standard deviations for the respective mean values.
Each vertical bar represents standard deviations for the respective mean values.
Table.8. Correlation coefficient between selected variables and life cycle energy of each house Simple house Variables 1 2 3 4 4 5 6 8 9
Medium houses
r-value
Sig.
0.86 0.81 0.76 0.42 0.17 0.16 0.14 0.08 0.07
** ** ** ** * * -
Total floor area Household income Refilling cooking gas Lot area Number of TV Household size Duration of living House’s storey Building age
Variables Total floor area Household income House’ s storey Number of TV Refilling cooking gas Lot area Household size Duration of living Building age
Luxurious houses
r-value
Sig.
0.89 0.85 0.49 0.47 0.37 0.28 0.27 0.22 0.17
** ** ** ** ** ** ** * *
Variables Total floor area Household income Number of AC Building age Duration of living Refilling cooking gas Number of TV Household size Lot area
r-value
Sig.
0.93 0.79 0.57 0.53 0.33 0.32 0.21 0.20 0.14
** ** ** * * -
* = Significant at 5% level; ** = Significant at 1% level
Table.9. Coefficient of variables included in regression equation for each house (life cycle energy) Simple house Variables 1 2 3 4 5
Total floor area Household income Refilling cooking gas House’s storey Lot area Constant R2
Unstandardized
Standardized
coefficient
coefficient
1.57 0.13 4.99 82.18 0.86
0.50 0.28 0.27 -
* = Significant at 5% level; ** = Significant at 1% level
Medium houses Sig. ** ** ** -
Unstandardized
Standardized
coefficient
coefficient
2.22 0.41 97.54 0.13 -2.43 0.90
0.52 0.39 0.18 0.08
Luxurious houses Sig. ** ** ** *
Unstandardized
Standardized
coefficient
coefficient
5.50 323.02 0.86
0.93 -
Sig. ** -
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Life Cycle CO2 Emissions. The embodied CO2 emissions were calculated through multiplying the energy consumption for each fuel type by its corresponding CO2 emission factor (Fig. 7.). The estimated embodied CO2 emissions for simple, medium and luxurious houses are 3.1, 11.5 and 31.6 tons CO2-eq respectively. Similarly, the CO2 emissions during the operation phase were computed as shown in the same figure. The estimated CO2 emissions of the operational phase for simple, medium and luxurious are 29.7, 80.1 and 251.0 tons CO2-eq respectively. The CO2 emissions during operation phase are greater than the embodied CO2 emissions by 7 to 10 times. Summary A survey was conducted in Bandung, Indonesia, in 2011 in order to analyze life cycle energy and CO2 emissions within unplanned houses in the city. The actual on-site measurement was conducted to obtain building material inventory and household energy consumption data. (1) The results showed that the average embodied energy for simple, medium and luxurious houses was 36.3, 130.0, and 367.7 GJ respectively. The annual average operational energy of simple, medium and luxurious houses varied at 11.6, 17.4, and 32.1 GJ/year respectively. The cement and the cooking were the largest contributors of embodied and operational energy respectively for all houses. The operational energy tended to be greater than the embodied energy for respective houses by 4 to 7 times. The profiles of CO2 emissions showed the similar proportion with those of energy consumption. (2) The results of statistical analyses indicated that the embodied, operational and life cycle energy are predominantly determined by ‘total floor area’ and supported by some explanatory variables such as ‘household income’. This clearly shows that these dependent variables as well as life cycle CO2 in Indonesian unplanned houses can be predicted by the above variables with high accuracy. Acknowledgments This research was supported by a JSPS Grant-in-Aid for Young Scientists (B) (No. 23760551) and a grant from the TOSTEM Foundation for Construction Materials Industry Promotion. References [1] Bandung, Bandung in Figures, Agency for the Centre of Statistic of West Java, 2010. [2] Indonesia, The Ministerial Decree of Public Work, No. 45, 2007. [3] N.A. Utama and H. Sabir Ghewala, Life cycle energy of single landed houses in Indonesia, Energy and Buildings, 40 (2008) 1911-1916. [4] Z. Kurdi, et al., Determining factors of CO2 emissions in housing and settlement of urban area in Indonesia, Ministry of Public Work of Indonesia, 2006. [5] J. Monahan and C.J. Powell, An embodied carbon and energy analysis of modern methods of construction in housing: A case study using a life cycle assessment framework, Energy and Buildings, 43 (2011) 179-199. [6] K.M. Dixit, et al., Identification of parameters for embodied energy measurement: A literature review, Energy and Buildings, 42 (2010) 1238-1247. [7] Indonesia, Input-output table of Indonesia, Agency for the Centre of Statistic of Jakarta, 2005. [8] U. Surahman and T. Kubota, Development of simplified LCA model for residential buildings in Indonesia; A pilot survey in Bandung, AIJ Journal of Technology and Design, 18, No.40 (2012) 1003-1008.
