Hybrid input-output analysis for life-cycle energy consumption and carbon emissions of China’s building sector

Hybrid input-output analysis for life-cycle energy consumption and carbon emissions of China’s building sector

Building and Environment 104 (2016) 188e197 Contents lists available at ScienceDirect Building and Environment journal homepage: www.elsevier.com/lo...

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Building and Environment 104 (2016) 188e197

Contents lists available at ScienceDirect

Building and Environment journal homepage: www.elsevier.com/locate/buildenv

Hybrid input-output analysis for life-cycle energy consumption and carbon emissions of China’s building sector Xiaocun Zhang a, Fenglai Wang b, * a b

School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin 150090, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 4 March 2016 Received in revised form 4 May 2016 Accepted 13 May 2016 Available online 14 May 2016

With respect to global climate change, energy consumption and carbon emissions of the building sector has become an increasingly crucial issue in the sustainable development of China. While process-based analyses have been performed in previous research, in the present study, we propose a hybrid inputoutput approach that could account for supply-chain energy and emissions by China’s building sector. In terms of energy and emission sources, three scopes are defined, primarily aimed at the entire life-cycle of building sector. By dividing the life-cycle into construction, operation, and disposal stages, both scopebased and stage-based analyses are made using domestic statistical data, within the range 1997e2012. The results demonstrate that supply-chain energy and emissions of Scope 3 contribute significantly to the overall life-cycle impacts of building sector, which might be underestimated in a process-based assessment. Although the operation stage appears to be the one with the largest consumption and emissions in the lifespan of a single building, attention should also be paid to the construction stage. The energy and emissions during construction make up the largest share (over 60%) in the life-cycle of the building sector due to the large number of building projects every year. Energy and carbon-intensive components are also evaluated, and possible measures for energy-saving and carbon reduction are discussed. Accordingly, this study provides some useful methods and relevant analysis results, which will be critical for the future of sustainable development of China’s building industry. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Building sector Life-cycle assessment Carbon emission Energy consumption Hybrid input-output analysis

1. Introduction 1.1. Research background According to The Intergovernmental Panel on Climate Change’s Fifth Assessment Report (IPCC AR5) [1], the global average temperature increased by 0.85  C from 1880 to 2012. In light of the serious consequences of global climate change, the issue of greenhouse gas (GHG) emissions has attracted increasing attention [2]. As a developing country with a large population, the total energy consumption and carbon emissions of China are among the highest in the world [3e5]. In tandem with the rapid development of its economy, China has a significant responsibility for reducing global carbon emissions, and has already made a commitment to

* Corresponding author. Room 521, School of Civil Engineering, Harbin Institute of Technology, Haihe Road 202#, Nangang District, Harbin 150090, Heilongjiang Province, China. E-mail address: fl[email protected] (F. Wang). http://dx.doi.org/10.1016/j.buildenv.2016.05.018 0360-1323/© 2016 Elsevier Ltd. All rights reserved.

reduce carbon emissions per GDP by 40e45% by 2020, compared with the level in 2005 [6]. Because it is one of the most energy and carbon-intensive industries, the building sector accounts for roughly 30e40% of the total energy consumption worldwide, and this sector contributes over one third of global CO2 emissions [7e9]. Different from developed countries, except for the huge amounts of energy and emissions for daily operation of buildings, China is presently dealing with an excessively large number of building projects during the process of urbanization [10]. This consequently leads to a dramatic growth of energy use and emissions for construction work [11]. Accordingly, comprehensive analyses of the energy consumption and carbon emissions of China’s building sector throughout the life-cycle have been imperative for energy-saving and carbon reduction. 1.2. Life-cycle assessment of buildings Life-cycle assessment (LCA) has become a widely acknowledged tool for the research of environmental impacts. With respect to the

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lifetime of a building, components such as materials production and transportation, building construction and operation, demolition work, and waste treatment are usually taken into account for both macro-level and micro-level analyses. Process-based and input-output based approaches (P-LCA and IO-LCA) are two fundamental ideas in analysis [11e14]. P-LCA is able to achieve detailed information for each process involved in each scope [11], but P-LCA has certain truncation error due to the definition of system boundary of buildings [15]. On the other hand, IO-LCA can capture the energy and carbon footprint from the entire supplychain [13]. However, IO-LCA also introduces uncertainties, because the sectors in IeO analysis can only represent typical processes [12]. Previous studies have made many attempts to investigate lifecycle energy use and carbon emissions of single buildings, using process-level data. For example, Gustavsson and Joelsson [16] compared the life-cycle primary energy use and CO2 emissions of wood-framed buildings and concrete buildings. You et al. [17] assessed the life-cycle emissions of urban residential buildings in China, covering processes of materials production, on-site construction, building operation, and demolition. Davies et al. [18] and Luo et al. [19] analyzed the embodied energy and carbon of office buildings based on case studies. Abanda et al. [20], Islam et al. [21], and Chau et al. [22] have also conducted studies reviewing the lifecycle energy and carbon assessment of buildings. IeO based case studies were also made by some researchers. Han et al. [23] proposed an IeO model for carbon analysis of construction activities and compared several methods for groundwork. Shao et al. [24] analyzed the energy use and carbon emissions for construction of six case study buildings in Beijing, China, based on the bill of quantities (BOQ). Chang et al. [25] calculated the embodied energy for different types of buildings using the average materials consumption data in the construction phase. Besides, facing the crucial issues regarding energy-efficiency and carbon mitigation, a large number of strategies were proposed for building life-cycles. Lomas [26] and Abdallah et al. [27] proposed measures for carbon reduc a kova  et al. tion and energy conservation in existing buildings. Cul [28] investigated energy-saving and carbon reduction strategies for construction of building structures. Ng et al. [29] summarized possible approaches for buildings that would remain low-energy and low-carbon throughout their life-cycle. However, due to the inconsistency of methods and databases, micro-level studies focusing on selected buildings could hardly reflect the overall characteristic of regional buildings with respect to history. Unfortunately, although IO-based methods are well applied to study environmental performance of national economy at macro-level [30e32], research on the regional building sector is €sse n [15] assessed the relatively less, especially for LCA studies. Na energy use and carbon emissions during the construction stage of buildings. Acquaye and Duffy [33] estimated the GHG emissions of the Irish construction sector. Onat el al [12]. investigated the lifecycle carbon footprint of U.S. buildings according to the World Resource Institute (WRI) standard. Using multi-regional IeO analysis, Hong et al. [34] found that the construction industry contributed 29.6% of the total energy use in China for 2007.

189

Given that the life-cycle pertains to the entire inventory of buildings, it might be called the conglomerate building life cycle. First in Section 2, a hybrid IO-LCA approach and relative data processing procedure are proposed which could account for both on-site and supply-chain activities. Then in Section 3, Chinese statistical data for 1997e2012 are analyzed, and the scope-based and stage-based results for conglomerate life-cycle of the building sector are discussed. Finally, possible measures for energy-saving and carbon reduction are exemplified. A summary of the analytical framework of the present study is illustrated in Fig. 1. 2. Methodology and data 2.1. Research scopes The building life-cycle was divided into three stages in the present study, namely construction stage, operation stage, and disposal stage. Both the direct physical inputs (direct energy consumption and carbon emissions by building sector) and indirect inputs (from the upstream supply-chain) were considered, using a hybrid approach consisting of process method and input-output analysis. Moreover, in order to conduct a comprehensive analysis of the energy consumption and carbon emissions, the research scopes were set to three different levels proposed by WRI [12,14,35]. Scope 1 referred to the on-site energy consumption and carbon emissions produced by fossil fuel combustion. Scope 2 represented the energy consumption and carbon emissions from the production of purchased electricity and heat, namely the fossil fuel combustion in power plants. Scope 3 referred to all the other energy consumption and carbon emissions generated from the economic supply-chain such as building materials preparation and transportation. Fig. 2 illustrates the relationship of the three scopes and the life-cycle stages of buildings in detail. Based on process-level data of direct energy use of the building sector, the energy consumption and carbon emissions of Scope 1e2 could be calculated using a simple P-LCA approach, whereas these of Scope 3 had to be estimated using a IO-LCA approach to account for physical inputs of upstream activities. Furthermore, for Scope 2,

1.3. Objectives and organization In light of the above mentioned gaps in knowledge, the present study aimed to achieve a comprehensive analysis of life-cycle energy consumption and carbon emissions of China’s building sector (entire national inventory of buildings) from a macro-level perspective. As introduced in Section 1.2, both P-LCA and IO-LCA have their advantages and limitations. Hence, a hybrid method covers their complementary strengths might be a good practice.

Fig. 1. Analytical framework of the present study: The definition of scopes is presented in Section 2.1, data source is introduced in Section 2.4.

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Fig. 2. Relationship of the three scopes and life-cycle stages of buildings. CON, OPE, and DIS denote the construction stage, the operation stage, and the disposal stage, respectively.

carbon emissions are generated in power plants, while electricity and heat are transformed in power plants but finally consumed within buildings. As a result, in previous studies [36], Scope 1 carbon emissions were usually taken as direct emissions, and Scope 2e3 carbon emissions were referred to as indirect emissions (or supply-chain emissions), the energy consumption of Scope 1e2 was considered as direct consumption, and that of Scope 3 was defined as indirect consumption.

2.2. Process-based data analysis Direct Scope 1 carbon emissions can be calculated based on the fossil fuel consumption data and relevant emission factors using the methods proposed in IPCC 2006 [37], while the energy use can be standardized as coal equivalents (one tce corresponds to 7000 kcal, which is commonly used in China), according to the conversion factors based on calorific values:

Ctotal ¼

n X ðFCi $EFi Þ

(1)

i¼1

Etotal ¼

n X ðFCi $li Þ

(2)

i¼1

where n is the total number of fossil fuel types for direct use; Ctotal and Etotal are the carbon emissions and energy consumption of Scope 1, respectively; FCi is the amount of type i fossil fuel combusted; EFi and li are the carbon emission factors and energy conversion factors, respectively, of type i fossil fuel. The Scope 2 carbon emissions and energy consumption (purchased electricity and heat by building sector) can also be assessed using the above mentioned approach, while the emission factors and energy conversion factors for power generation can be estimated using the annual energy balance tables of China as follows:

EFpro ¼

m  X  1 FCpro;j $EFj $Epro

m  X  1 FCpro;j $lj $Epro

2.3. Input-output data analysis IeO analysis is an important method of macro-level economic research, and a powerful tool for the study of sectoral energy consumption and carbon emissions. This form of analysis can take the intermediate physical flows among sectors into account. The original economic IeO table was extended (see Table 1) to add the physical inputs, where Xi, Yi, Xij, and Nj represent sectoral total output, sectoral final demand, intermediate use, and sectoral value added, respectively; dij and Fi is the direct carbon/energy input of sector i due to the intermediate use and final use of sector j, respectively; and Dd,i is the total direct carbon/energy input of sector i, which can be calculated according to the process-based approach as presented in Eqs. (1)e(4). Based on the general equilibrium concept of “Input ¼ output” in the Leontief quantity model [38], a matrix balance equation describing the relationship between total output and final demand for sector i can be expressed as:

X ¼ ðI  AÞ1 $Y ¼ L$Y

(3)

(4)

j¼1

where m is the total number of fossil fuel types for power generation; EFpro and lpro are the emission factors and energy conversion factors, respectively; FCpro,j is the fossil fuel inputs for power

(5)

where X ¼ ½Xi n1 and Y ¼ ½Yi n1 are column vectors representing the total output and final demand, respectively, A ¼ ½xij =xj nn is the direct consumption matrix of production coefficients, and L ¼ ½lij nn is the Leontief inverse square matrix. According to Table 1, the direct physical input of sector i can be described as:

Dd;i ¼

n X

0 dij þ Fi ¼ εi [email protected]

j¼1

j¼1

lpro ¼

generation; and Epro is the production of secondary energy (electricity or heat). It should be pointed out that standardization of electricity and heat using Eq. (4) referred to a method based on equivalent caloricity which has accounted for the conversion efficiencies.

n X

1 Xij þ Yi A

(6)

j¼1

where εi is the direct physical input per unit total output of sector i. Considering Dd ¼ ½Dd;i n1 and b ε ¼ ½b ε ij nn (b ε ij ¼ εi when i ¼ j, and b ε ij ¼ 0 when i s j), a matrix equation can be summarized as follows, combined with Eq. (5):

Dd ¼ b ε $X ¼ b ε $L$Y

(7)

Eq. (7) clearly describes the relationship between direct carbon inputs and sectoral final demands, while the coefficient matrix b ε $L indicates the inner physical flows among sectors for the production

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191

Table 1 Extended IeO table for energy and carbon emission analysis. Input

Output Intermediate use

Economic inputs

Sector 1 Sector 2 … Sector n

Value added Physical inputs

Sector 1 Sector 2 … Sector n

Sector 1

Sector 2



Sector n

x11 x21 … xn1

x12 x22 … xn2

… … … …

x1n x2n … xnn

N1

N2



Nn

d11 d21 … dn1

d12 d22 … dn2

… … … …

d1n d2n … dnn

activities driven by final demand. Furthermore, the supply-chain carbon/energy intensity of sector j, which only took consideration of the upstream inputs, zj can be derived as:

zj ¼

n X

εi lij

(8)

i¼1;isj

Then the corresponding supply-chain carbon/energy, Ds,j can be calculated as:

Ds;j ¼ zj Yj

(9)

Moreover, the carbon emission factors of imports were assumed to be the same as those of domestic products [39,40], for the following three reasons: (1) an assumption of ‘carbon avoided’ was applied, which represented the hypothetical emissions generated if all imported products were produced domestically, and relevant analysis results of building sector carbon emissions would be closer to the domestic technical level; (2) the IeO table of China did not have detailed flow matrices for intermediate use of imports; some inaccurate assumptions had to be made to count the import carbon flows [41,42]; and (3) China has dozens of trading partners which made it very difficult to give reasonable emission factors for the imports of each sector. 2.4. Data collection 2.4.1. Energy consumption and carbon emissions for economic sectors The statistical data for direct energy consumption organized by sectors were derived from “China energy statistical yearbook” (CESY, 1998e2013) [43], mainly including coal, coke, coal gas, petroleum products, LPG, refinery gas, and natural gas as fuels, while excluding the energy inputs as raw materials and solvents (e.g., white spirits and petroleum asphalt). Three fundamental sources of carbon emissions were taken into consideration in the present study, namely fossil fuel combustion, agricultural activities, and industrial activities. The carbon emission factors of fossil fuels involved in the statistical energy balance tables are presented in Table 2. For the purpose of consistency with China’s energy situation, carbon content, net calorific value, and the fraction of oxidized carbon were derived from official data released by domestic governmental departments (mainly including “Guideline for Provincial Greenhouse Gas Inventories” [44] and “Statistical System of Energy Consumption in Public Institutions” [45]). Meanwhile, default values for CH4 and N2O emissions in IPCC 2006 [37] were referred to, and GWP (global warming potential) was adopted to determine the carbon emission equivalents, as 1: 28: 265 for CO2: CH4: N2O (as recommended in IPCC AR5) [1].

Final demand

Total output

Y1 Y2 … Yn

X1 X2 … Xn

F1 F2 … Fn

Dd,1 Dd,2 … Dd,n

Table 2 Carbon emission factors of fossil fuels. Fuel

Carbon emission factor

Raw coal Cleaned coal Other washed coal Briquette Coke Coke oven gas Blast furnace gas Converter gas Petroleum Gasoline Kerosene Diesel Fuel oil LPG Refinery gas Natural gas LNG Other petroleum products Other coking product

1.9901 tCO2e/t 2.4166 tCO2e/t 0.9590 tCO2e/t 2.3244 tCO2e/t 2.8648 tCO2e/t 8.2543 tCO2e/104 m3 9.6731 tCO2e/104 m3 14.3091 tCO2e/104 m3 3.0274 tCO2e/t 2.9355 tCO2e/t 3.0439 tCO2e/t 3.1063 tCO2e/t 3.1806 tCO2e/t 3.1041 tCO2e/t 3.0144 tCO2e/t 21.6714 tCO2e/104 m3 3.1817 tCO2e/t 2.9551 tCO2e/t 2.8725 tCO2e/t

Carbon emissions sourced from agricultural and industrial activities were assessed on the basis of the methods and coefficients provided by Ref. [44]. Primary data for production and activities was obtained from “China statistical yearbook” (CSY, 1998e2013) [46]. Although restricted by the detail of the statistical data, six kinds of fundamental processes in various sectors were considered, including: (1) grain planting, (2) nitrogen fertilizer use, (3) intestinal fermentation and manure management, (4) coal, oil, and natural gas extraction, (5) cement clinker production, and (6) ironmaking and steel-making. Moreover, based on the emission and energy scopes coordinated with that defined in Section 2.1, it should be emphasized that electricity and heat consumption were directly allocated by purchased sectors, while related carbon emissions were counted in power generation sectors and distributed by other sectors as supply-chain emissions in the extended IeO models. 2.4.2. Economic IeO tables The basic economic IeO table is compiled by the National Bureau of statistics of China (NBS) every five years, and a supplementary version with fewer details is updated during this period. In the present study, seven nationwide IeO tables (for 1997, 2000, 2002, 2005, 2007, 2010, and 2012) with a varying number of economic sectors (124, 17, 122, 62, 135, 65, and 139, respectively) were adopted for comprehensive research of the building industry. A key challenge for data processing was that the classification of economic sectors in the IeO tables and that of energy consumption

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(carbon emission) data for each year was not entirely the same, which led to incompatibility between b ε and L in the extended IeO model (Eq. (7)). Two alternative approaches were proposed by Su et al. [41] for data treatment. The first was to aggregate the incompatible sectors to the level that both datasets could satisfy, while the other was to disaggregate the physical input data to match the IeO tables using a prorated distribution method based on sectoral economic outputs. While the first scheme can guarantee the accuracy of aggregated data without potential errors caused by extra assumptions, the latter scheme can retain more detailed information from the IeO tables. This is valuable for the analysis of supply-chain energy consumption and carbon emissions of the building sector, and was adopted in the present study. 2.5. Analysis of the building sector conglomerate life-cycle 2.5.1. Building construction and disposal stages Detailed sub-processes were defined for the analysis of the building construction and disposal stages as shown in Table 3. CESY [43] provided the terminal direct energy consumption data of the building sector, which includes both on-site construction and building demolition activities. Based on the hybrid approach introduced above, physical flows of the whole supply-chain for onsite activities can be obtained. With an assumption that the energy use of building demolition is about 9% of that of building construction [11,47], the physical flows can be further disaggregated. For other sub-processes that only related to supply-chain inputs, extended IeO analysis can be performed. A summary of the above calculations are also presented in Table 3. 2.5.2. Building operation stage Energy consumption and carbon emissions at the operation stage mainly come from heating, cooling, lighting, cooking, and appliances [10e12]. In light of the structure and characteristics of statistical energy data in China [43,46], buildings were divided into three categories in the present study (i.e., urban public buildings, urban residential buildings, and rural residential buildings). Therefore, on the basis of the energy balance tables, related energy and emissions of Scope 1e2 could be calculated accordingly, using the method proposed in Section 2.2. The details for data treatment are shown in Table 4. Furthermore, Scope 3 supply-chain energy and emissions at the operation stage are mostly related to production and supply of energy. These can be calculated as follows. First, calculate the monetary value of consumed energy based on the annual statistical energy price. Second, input the monetary value into the extended IeO models, and calculate the overall physical inputs. Finally, subtract the direct inputs from the total values to obtain the supplychain inputs.

3. Results and discussion Based on the proposed methods introduced above, life-cycle energy consumption and carbon emissions of China’s building sector were studied for the range of years selected. The results of scope-based analysis, stage-based analysis, and some strategies to save energy and reduce carbon during building life-cycles, are presented in the following sub-sections. 3.1. Scope-based analysis of the building sector The cumulative energy consumption and carbon emissions of the three research scopes for the building sector in China are shown in Fig. 3. The results indicate that, both energy consumption and carbon emissions have increased significantly since 1997, with relatively slow growth from 1997 to 2005, and rapid growth after 2005, especially for Scope 2e3. The total amount of energy and emissions of 2012 are nearly three times those of 1997. Fig. 3 illustrates that Scope 3 is the largest contributor to total energy and emissions with average shares of 63.5 and 68.9%, respectively; followed by Scope 2 with shares of 20.0 and 18.2%, respectively. Furthermore, direct energy use and carbon emissions only count for 36.5% and 31.1%, respectively, however these are the driving factors for the supply-chain inputs. The overall results point out that the indirect energy use and carbon emissions driven by the building sector have negligible impacts on the total amount, which might be underestimated in the process-based LCA analysis. 3.2. Stage-based analysis of the building sector 3.2.1. Energy and emissions of construction stage Fig. 4 indicates the components of the construction stage and their contribution to the total energy and emissions of domestic projects. An overall trend of increase for the construction stage can be observed in Fig. 4. Materials preparation is one of the driving sources for both energy and emissions, with an average share of 60.7% and 47.9%, respectively. Manufacture of cement, lime, gypsum, iron, steel, and their products are the main contributors that make up 71.1% and 88.1% of the energy and emissions for materials preparation, respectively. However, the lower percentage for energy use indicates that non-energy emissions of industrial activities have notable influences. Energy production and supply is another crucial source at the construction stage. Because carbon emissions from electricity and heat generation was included in the energy sectors, a relatively higher contribution of energy supply is indicated in Fig. 4 for emissions (38.7%) rather than energy consumed (16.2%). Furthermore, with respect to energy use for on-site construction work, they only account for a proportion of 4.4% and 3.3%, for the total energy and emissions, respectively.

Table 3 Physical flows at the construction and disposal stages. Stage

Process

Construction Building materials preparation Construction On-site construction activities Construction Transportationa Construction Supply-chain energy supplyb Construction others Disposal Building demolition Disposal Waste transportationa Disposal Waste treatment a b

Scope Method 3

Supply-chain inputs related to materials and equipment manufacturing sectors

1e3 3 3 3 1e3 3 3

Hybrid IeO analysis based on direct energy consumption data, (building sector inputs defined by CESY)  (1/1.09) (Supply-chain inputs related to transportation sectors)  93% Supply-chain inputs by energy sectors Supply-chain inputs by other upstream sectors Hybrid IeO analysis based on direct energy consumption data, (building sector inputs defined by CESY)  (0.09/1.09) (Supply-chain inputs related to transportation sectors)  7% Supply-chain inputs related to waste treatment sector

According to existing studies [11] at process-level, waste transportation contributes approximately 7% on average to the total transportation phase. According to the definition of IeO models, supply-chain energy supply not only directly relates to building sector, but also counts in other upstream sectors.

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Table 4 Statistics for energy consumption and carbon emissions at the building operation stage. Building typea

Urban public buildings Urban residential buildings Rural residential buildings

Sub-sectoral energy involveda

Relevant primary data in energy balance tables

b

Wholesale, Retail Trade, Hotel, Restaurants, and others Urban households Rural households

Scope1c

Scope2d

Coal, fuel gas, 5% gasoline, 35% kerosene and diesel Coal, fuel gas, 5% kerosene and diesel Coal, fuel gas, 5% kerosene and diesel

Electricity and heat Electricity and heat Electricity and heat

a

The building types were classified for ease of counting in sub-sectors provided by energy balance tables in CESY [43]. Energy consumed by sector of transport, storage, and post were excluded, because for most of these activities, energy use occurred outside the boundary of buildings. c Coal is mainly for individual household heating (and cooking in rural areas). Gaseous fuels mainly included coal gas, LPG, natural gas, and LNG, which are used for cooking and hot water. A large proportion of the oil consumption is used for transportation and non-energy use, which is excluded according to existing research results by WRI [35]. d Purchased heat is mainly used for centralized heating of urban buildings, while electricity is consumed by refrigeration equipment and household appliances. b

Fig. 3. Scope-based energy consumption and carbon emissions of building sector in China: (a) Energy consumption (108 tce); (b) Carbon emissions (108 tCO2e).

3.2.2. Energy and emissions of operation stage Fig. 5 shows the results of energy and related emissions at the building operation stage, organized by building types: urban public buildings, urban residential buildings, and rural residential buildings. As illustrated in Fig. 5, energy and emissions have risen dramatically since 2005, while similar increases can be observed for all three of the building types. Rural residences have an approximate share of 26% for total energy and emissions of all existing buildings, while urban residential and public buildings contribute 32% and 42%, respectively. Furthermore, the components of detailed energy consuming sources and their associative shares in three building types are also analyzed and illustrated in Fig. 6. It can be seen that heating and electricity are the dominant factors for both energy and emissions at the operation stage. With respect to the different functions of buildings, purchased electricity is the most influential energy source in public buildings, fuel gas (mainly for cooking) has considerable effect on urban residential buildings, while individual household heating contributes most to rural residential buildings. Besides, there is relatively small difference between the components of energy and emissions for the same type of buildings, which stresses the fact that all emissions at this stage are energy-related.

Fig. 4. Components of energy consumption and carbon emissions at construction stage: (a) Energy consumption (108 tce); (b) Carbon emissions (108 tCO2e).

3.2.3. Energy and emissions of disposal stage Processes of building demolition, waste transportation and waste treatment were considered at the disposal stage, and the results are shown in Fig. 7. Demolition and transportation of waste are the two main sources, accounting for over 95% of the total energy and emissions (except in 2010, see captions of Fig. 7). In the last decades, China has completed a large amount of construction and demolition work with the development of economy, and millions of tons of building waste were produced every year. However, waste treatment is found to have a negligible overall impact, because simple landfill treatment is applied to most of the waste, and the recycling rate for waste materials is only about 1% in China [48]. 3.2.4. Total energy consumption and carbon emissions Table 5 outlines the statistical results of stage-based energy consumption and carbon emissions of the building sector in China during 1997e2012. It can be concluded from Table 5, that the proportions of each stage attributed to the entire life-cycle remain nearly unchanged over this period. The construction stage takes the largest share with average percentages of 64.7 and 60.3% for energy and emissions, respectively. The operation stage is the second contributor with shares of 34.9 and 39.1%, respectively. On the

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Fig. 5. Components of energy consumption and carbon emissions at the operation stage organized by building types: (a) Energy consumption (108 tce); (b) Carbon emissions (108 tCO2e).

Fig. 6. The components of energy consuming sources at the operation stage: The bar chart shows the average proportion of each source over the interval 1997e2012. EU and CE denote energy consumption and carbon emissions, respectively.

other hand, energy and emissions of the disposal stage contribute less than 1% to the life-cycle, which is also observed in both process-based and IO-based analysis previously [12,49]. Besides, it should be noted that the share of the operation stage to total emissions is higher in the present study than a previous processlevel analysis (about 25%) proposed by Zhang et al. [11]. This is because dramatic supply-chain emissions for energy production and supply were considered in the calculations. The increased overall energy and carbon emissions of the building sector contributed nearly 50% (on average) to the total for China. The life-cycle data presented in Table 5 is the annual energy consumption and carbon emissions for all buildings in China, which is conceptually quite different from that of a single building. However, life-cycle energy and carbon emission intensities based on the building area can be evaluated in the following ways: (1) for construction stage, through multiplying the embodied intensities in terms of monetary values in IeO analysis by average project cost per area provided by CSY [46]; (2) for operation stage, through dividing the energy and emissions by existing building area in use; and (3) for demolition stage, through dividing the energy and emissions by the annual demolition area.

Fig. 7. Energy consumption and carbon emissions of disposal stage: (a) Energy consumption (107 tce); (b) Carbon emissions (107 tCO2e). No data on waste treatment is available for 1997, 2000, and 2002, while that of 2010 includes the supply-chain emissions of sector “Manufacture of artwork and other manufacturing” in the IeO table, which makes it seem considerable.

With the above approach, average values for the life-cycle of buildings nationwide can be calculated. Fig. 8 outlines the results for energy and emissions per building area in 2012 as an example, where the lifespan of buildings in the analysis was taken as 50 years. The result indicated that the sequence of life-cycle intensities is urban public buildings, urban residential buildings, and rural residential buildings. The operation stage contributes most to energy use and emissions during the life-cycle, followed by the construction stage for all three building types. Furthermore, the components of life-cycle energy and emissions are very similar to that of P-LCA analysis [50e52], while slight differences can be observed (such as higher values for the construction stage) that might have resulted from additional consideration of supply-chain activities.

3.3. Hybrid analysis of the building sector Sections 3.1 and 3.2 present the analysis results based on scopes and stages of the comprehensive building life-cycle, respectively. Additional intersection studies were performed to divide the stagebased results further into scopes, which is valuable for making suggestions and decisions. The results for 2012 are illustrated in Fig. 9. As can be seen from Fig. 9, Scope 3 is the dominant source with shares over 95 and 50% at the construction and disposal stages, respectively. Whereas, for Scope 2, energy and emissions related to purchased electricity and heat had the largest share with 59 and 56%, respectively, at the operation stage. The above analysis clearly demonstrates the life-cycle energy consumption and carbon emissions of China’s national buildings within the period of 1997e2012. Hotspots for energy and emissions can be concluded for each component of the scopes and stages. In terms of the hotspots, the following section is mainly focused on energy conservation and emission reduction approaches.

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Table 5 Annual energy consumption and carbon emissions during building life-cycle in China. Year

1997 2000 2002 2005 2007 2010 2012

Carbon emissions (108 tCO2e)

Energy consumption (108 tce)

Construction

Operation

Demolition

Total

Construction

Operation

Demolition

Total

11.35 12.58 14.07 20.42 25.99 31.96 39.26

6.42 6.83 7.67 11.53 13.94 16.58 19.88

0.05 0.09 0.09 0.12 0.16 0.21 0.18

17.82 19.50 21.83 32.07 40.09 48.75 59.32

3.53 4.02 4.42 5.74 7.39 9.14 10.71

2.30 2.48 2.74 4.11 5.01 5.83 6.82

0.03 0.04 0.04 0.06 0.08 0.14 0.10

5.86 6.54 7.20 9.91 12.49 15.12 17.63

building performance. As a result, it is still necessary to put stress on the construction methods. Nowadays, prefabrication of building structures has become popular in China, for the purpose of reducing on-site waste and manpower. Attention should also be paid to accessional transportation of precast members, because transport over a long distance could largely offset the overall reductions of energy and emissions [53]. On the other hand, in tandem with the economic development of China, a large amount of buildings are newly constructed every year, which is the most essential reason for the growth of energy and emissions of the building sector. Reasonable layout for urban planning, and effective use of the existing building stock might be good practices to control this rapid growth.

Fig. 8. Life-cycle energy consumption and carbon emissions per building area of 2012 (unit: tce/m2 for energy, tCO2e/m2 for emissions): RR, UR, and UP represent rural residential buildings, urban residential buildings, and urban public buildings, respectively. The data for the disposal stage is the average value of three building types, and the data for urban building construction is the average of UR and UP.

3.4.2. Suggestions for the operation stage Purchased electricity is a major energy and emission source in the operation stage of buildings. Two practical routes could be considered: (1) enhancing the management and awareness of energy-saving [54], especially in public buildings, as indicated in

Fig. 9. Components of stage-based energy consumption and carbon emissions of the building sector: (a) Energy consumption; (b) Carbon emissions.

3.4. Suggestions for energy conservation and emission reduction 3.4.1. Suggestions for the construction stage Based on the above mentioned analysis, steel and cement contribute significantly to supply-chain energy and emissions of the construction stage. With the progress of technology, the comprehensive energy consumed for production of steel and cement has been reduced in recent years [43]; however they are still much higher than in developed countries (about 13% higher than in Japan around 2010). Moreover, from the perspective of planning and design of projects, reducing material inputs through optimization of building schemes could be a helpful way to cut down the energy and emissions [10]. Despite the fact that on-site work only contributes a small share (<5%) to the energy and emissions in the construction stage; they have crucial impacts on materials consumption and subsequent

Fig. 6; (2) making further use of renewable energy for power generation. Due to natural conditions, coal has been the primary energy source (share > 70% [46]) for a long time in China (especially in the north), which is both less-efficient and carbon-intensive. Heating is another main energy source at the operation stage. Previous studies have shown that a biomass-based system of regional cogeneration [55] could be a good practice for the implementation of energy-saving. More specifically, the centralized heating approach is better applied in urban buildings, and in rural areas where this is not suitable due to great transmission loss, solar power and biogas could be considerable energy sources. Finally, energy-efficient building designs might be helpful strategies for both newly-built and existing buildings. A large portion of existing buildings in China were constructed without any insulation measures at the end of last century. Hence, in accordance with the remaining service life, reasonable renovation for

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insulation of old buildings could play a positive role [56].

3.4.3. Suggestions for the disposal stage Recycling and reuse of waste materials should be emphasized when dealing with sustainable development of the building industry. Feasible practices such as reusing metal and wooden materials, and recycled concrete products, could greatly reduce the inputs for raw materials production, and consequently achieve advantages of low energy and emissions [28,57].

4. Conclusions In the present paper, we propose a hybrid input-output approach for the assessment of life-cycle energy consumption and carbon emissions of China’s building sector (entire national building inventory) covering the period from 1997 to 2012. This conglomerate building life-cycle was divided into construction, operation, and disposal stages. Both direct energy and emissions by building sector, and supply-chain inputs by upstream activities were considered, in accordance with the research scopes by which the energy and emission sources could be clearly described. Overall, a comprehensive analytical framework was established to trace the energy and carbon footprint of the building sector. Domestic statistical data was applied throughout the study, and the results indicated that, within the time range of the study, energy consumption and carbon emissions of China’s building sector have increased significantly, especially after 2005. Scope 3 was found to have the largest contribution to overall energy and emissions of the building sector, and might be underestimated in process-based research. With respect to stage-based results, the construction stage had the largest share (>60%) in the whole building sector. The operation stage stood out, assuming an average building life-cycle (lifespan) of 50 years, whereas the disposal stage could be neglected at present, from both energy use and carbon emission aspects. Considering further the temporal perspectives of carbon emissions (cumulative impacts over time), the construction stage should be emphasized in the context of carbon reduction and energy conservation, particularly for China, which is conducting extensive construction work. Possible approaches for controlling energy use and carbon emissions were also discussed, in terms of all scopes and stages of the conglomerate building life-cycle. Energy and carbon-intensive components such as production of cement and steel, consumption of purchased electricity, and energy consumed for heating were stressed in the analysis. Practical measures were summarized, including new construction methods, enhancing application of renewable energy, energy-efficient building designs, and recycling and reuse of waste materials. Furthermore, scope-based results indicated that China should adjust its industrial structure, to reduce supply-chain energy and emissions (Scope 3) by building sector. The methods presented here could be helpful for macro-analysis of the building sector in China, and the results could show the characteristic and main sources of life-cycle energy consumption and carbon emissions, which is valuable for decision making of reduction strategies. Moreover, certain limitations should also be noted: first, some assumptions were applied (proposed by previous studies) in analysis due to the lack of relevant statistical data, and should be improved along with the enrichment of data source; and second, analysis in the present study was performed on a nationwide scale. However, more detailed research at the provincial level could be accomplished using the proposed methods in future studies, which might be more helpful when considering regional features.

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