International Journal of Sustainable and Green Energy
Volume 4, Issue 3, May 2015, Pages: 85-91

Study on Energy Efficiency and Measurement of CO2 Emissions on Buildings: A Case Study in Hebei, China

Lei Wen1, 2, Ye Cao1, *

1Department of Economics & Management,North China Electric Power University, Baoding, Hebei, China

2The Academy of Baoding Low-Carbon Development, Baoding, Hebei, China

Email address:

(Lei Wen)
(Ye Cao)

To cite this article:

Lei Wen, Ye Cao. Study on Energy Efficiency and Measurement of CO2 Emissions on Buildings: A Case Study in Hebei, China. International Journal of Sustainable and Green Energy. Vol. 4, No. 3, 2015, pp. 85-91. doi: 10.11648/j.ijrse.20150403.13


Abstract: Research on energy efficiency and measurement of CO2 emissions on buildings, is crucial for taking countermeasures against climate change and identifying low carbon pattern in buildings of Hebei. Energy efficiency directly influence CO2 emissions. This paper presents two measurement methods of CO2 emissions, including the measurement from top-down using energy balance sheet and the measurement from bottom-up regarding structure decomposition of energy consumption of various service demand. Meanwhile, this study decomposes the energy consumption of buildings into detailed categories of service demands to explain energy efficiency, such as cooling, household appliance, domestic hot water and cooking in urban and rural residence except for central heating. Results reveal that energy consumption and CO2 emissions in urban, rural and public buildings maintain continuous growth reaching a highest year-increasing rate 18.07% in 2010. Specifically, public buildings show an extreme increasing rate with a total CO2 emissions of 208.45 million tons. Besides, CO2 emissions in cooling and cooking reach higher than other service demand. Eventually, policy implications are provided to mitigate the growth of CO2 emissions and identify energy efficiency strategies in Hebei.

Keywords: CO2 Emissions, Energy Efficiency, Buildings, Measurement


1. Introduction

Since 2004, global CO2 emissions burned by fossil fuels have accounted for 56.6% of greenhouse gas emissions. In addition, China’s CO2 emissions from fossil energy accounted for as high as 26.38% of the world's total and ranked the first with absolute predominance [1]. Copenhagen agreement in 2009 has urges China solemnly to pledge a significant cut in carbon intensity by at least 40% by 2020 from 2005 level. Since Copenhagen agreement, energy efficiency issue and greenhouse gases growth, has made China a focal point for criticism.

As a critical part, buildings released a lower CO2 in the process of construction and a higher CO2 due to the pull effect on majorities of other industries, accounting for 50% of the total CO2 emissions. Therefore, the application of more accurate method to measure CO2 emissions on buildings sector and then decompose impact components are crucial in promoting low-carbon buildings. Development and Reform Commission of China established a Low-carbon City policy and announced the selection of five provinces and eight cities to pilot low-carbon development work [2-6]. As an economy-developed province in China, Hebei ranks the sixth with GDP reaching 2019.71 billion yuan in 2010. Moreover, as economic development is highly dependent on energy consumption, the latter has also increased to 25418 million tons on standard coal in 2009. In this context, research on the measurement of CO2 emissions on buildings of Hebei in China has experienced a remarkable impetus.

This paper presents two measurement methods of CO2 emissions, including the measurement from top-down by the energy balance sheet and the measurement from bottom-up regarding structure decomposition of energy consumption of various service demand on building sector. The paper is structured as follows. Section 2 presents an overview of the main methods related to the measurement from top-down and bottom-up. In section 3, the data source is reported. Section 4 draws the result and discussions followed by conclusions and implications in section 5.

2. Methodologies

This paper conforms to international general classification and decomposes buildings sector into residential buildings and public buildings. Meanwhile, residential buildings can be divided into urban and rural residence buildings, seen as Figure 1.

Figure 1. Buildings sector after redivision.

2.1. The Measurement From Top-Down

Energy balance sheet intuitively reveals balance between energy resources, conversion and final consumption judged by data. Accordingly, energy consumption in buildings involve in four factors, namely consumption in central heating, urban residence except for central heating, rural residence except for central heating, and public buildings except for central heating. In addition, energy consumption in central heating are overall derived from heating production sector thus been calculated in heating production sector. Table 1 shows the adjustment method of energy consumption in buildings of Hebei [7].

Table 1. The measurement from top-down in buildings of Hebei.

Sector Sectors in energy balance sheet Adjustment method
Urban Buildings Final consumption in urban living Various energy consumption except for all gas and 95% diesel oil
Rural Buildings Final consumption in rural living Various energy consumption except for all gas and 95% diesel oil
Public buildings Final consumption of wholesale, retail, hotels and catering industry in tertiary industry Various energy consumption except for 95%gas and 35% diesel oil
Final consumption of other industry in tertiary industry Various energy consumption except for 95%gas and 35% diesel oil
Final consumption of transportation, storage, mail industry in tertiary industry 15% electricity consumption

2.2. The Measurement from Bottom-Up

The measurement from bottom-up, typically taking energy service demand and technology level into account, is to break down the structure of all sectors energy consumption [8]. Calculating steps and formulas are shown in Table 2.

(1) The combination of technologies for achieving specific energy service demand is calculated as follows:

(1)

where Pi is the demand quantity for energy service demand I; Pt,i presents the demand quantity for energy service demand i by technology t; i is the type of energy-service demand, such as building lighting in urban, steel demand quantity etc; t denotes the type of technology, such as building lighting in cities including incandescent, energy-saving lights, LEDs.

(2) Total energy consumption for all sectors energy-service demand is calculated as follows:

(2)

where E denotes the total energy consumption for all sectors energy-service demand (ton standard coal); Fn,t,I presents the energy consumption of N during the process of meeting energy service demand. N is energy types, such as electricity, coal, natural gas etc.

(3) Emissions that satisfy the sector’s energy-service demand are calculated as follows:

(3)

where CE is the CO2 emissions of this sector; EFn,t,I denotes emission factor of n in the process of meeting energy-service demand with technology t.

Table 2. The measurement from bottom-up in buildings of Hebei.

Sector Various categiories Adjustment method Emission factor
Urban buildings Cooling Ecool,u=∑Ei=∑H×EQi×Ti×Wi 0.9914 TCO2/MWh
Household appliance Ehapp,u=∑Ei=∑H×EQi×Ti×Wi
Domestic hot water Edome,u=∑Pu×1.3 2.62 TCO2/MWh
Cooking Ecook,u=∑Pu×4.5  
Rural buildings Cooling Ecool,u=∑Ei=∑H×EQi×Ti×Wi 0.9914 TCO2/MWh
Household appliance Ehapp,u=∑Ei=∑H×EQi×Ti×Wi
Domestic hot water Edome,u=∑Pr×1.3 2.62 TCO2/MWh
Cooking Ecook,u=∑Pr×4.5
Public buildings Operational Area of Catering Services Ecate,u=∑Mc×195   0.9914 TCO2/MWh
Operational Area of hotels Earea,u=∑Mo×195
Floor Space of Public Buildings Efloo,u=∑Mf×95

Note: E is total energy consumption of various categories (ton standard coal); Ei is energy consumption of equipment i(ton standard coal); H is the total households; EQi is ownership of household appliance i; Ti is the time using household appliance i(hours); Wi is the power of household appliance i(watts); I is equipment type, such as air-conditioning etc. P is the total person; M is the total area. Per capita domestic hot water demand coefficient is 1.3; Per capita cooking heating demand coefficient is 4.5 kgce/a. Big hotels and restaurants electricity consumption per unit area is 195(kWh/(m2·a)); large schoolspublic library electricity consumption per unit area is 95(kWh/(m2·a)).

3. Data Sources

The data for buildings is obtained from the Hebei Statistic Yearbook (2003–2012). Moreover, various coefficients of energy conversion and CO2 emissions are collected from the general principles of the comprehensive energy consumption calculation GB/T 2589-2008. In accordance with related departments, this study is accessed to Hebei statistical review and energy balance sheet, and then picks the methodology from IPCC guidelines for inventories. Besides, energy consumption multiplies emission factor is taken as 2.62 reference to China city greenhouse-gases inventory guide and per capita heating demand coefficient is reference to China city greenhouse-gases inventory Guide [9]. All unit is in 104 tons.

4. Results and Discussions

4.1. The measurement of CO2 Emissions from Top-Down in Buildings

Investigating Table 3 and Table 4, energy consumption of buildings reach the highest year-increasing rate at 18.07% in 2010; CO2 emissions of buildings approaches the highest annual growth rate at 18.08% in 2010. Both annual growth rate keep 6.75%.

Table 3. The energy consumption of buildings in 2003-2012.

  Urban Rural Public buildings
2003 525.666 585.988 195.905
2004 537.196 581.411 263.901
2005 544.338 598.850 459.806
2006 477.309 555.074 458.636
2007 462.097 556.941 509.988
2008 581.977 599.352 587.565
2009 613.533 586.167 602.870
2010 764.177 654.697 709.431
2011 787.182 664.551 773.103
2012 794.552 707.477 795.612

Table 4. The CO2 emissions of buildings in 2003-2012.

  Urban Rural Public buildings
2003 1377.244 1535.289 513.271
2004 1407.454 1523.297 691.421
2005 1426.165 1568.988 1204.693
2006 1250.550 1454.294 1201.625
2007 1210.694 1459.186 1336.169
2008 1524.781 1570.303 1539.421
2009 1607.456 1535.758 1579.519
2010 2002.143 1715.307 1858.709
2011 2062.416 1741.124 2025.529
2012 2081.727 1853.591 2084.505

Figure 2 shows a fluctuated trend of CO2 emissions in urban residence except for central heating, namely an upward trend in 2003-2005, followed by a little decreasing in 2006-2007 and finally a remarkable increasing. However, CO2 emissions in rural residence except for central heating, fluctuates around 15,800,000 tons; More specifically, owing to a improving living standard and then more utilization of heating radiator or small boiler etc, CO2 emissions shows a sharply increasing trend since 2010. CO2 emissions in public buildings except for central heating keeps increasing mainly in recent years, except for a little decline in 2006-2007.

Figure 3 presents the percentages of CO2 emissions from urban, rural and public buildings in 2003-2012. The percentage of in urban residence except for central heating, shows a cyclical changing trend, namely a little decrease in 2003-2007, followed by a little increase in 2008-2012. The percentage of in rural residence except for central heating mainly keeps decreasing, while the percentage of public buildings except for central heating shows an upward trend continuously. Therefore, the orientation of emission reduction has been urged toward public buildings except for central heating.

Figure 4 demonstrates CO2 emissions variations from various industries of public buildings in 2003-2012. Figure 5 shows the detailed percentage variations. Figure 4-5 illustrates that CO2 emissions of transportation, storage, mail industry wholesale, retail, hotels and catering industry and other industry in tertiary industry keeps stead increasing. Besides, CO2 emissions of transportation, storage, mail industry wholesale, retail, hotels takes up the majority of total CO2 emissions, accounting for 70%.

Figure 2. The bar chart of CO2 emissions from urban, rural and public buildings in 2003-2012.

Figure 3. Percentages of CO2 emissions from urban, rural and public buildings in 2003-2012.

Figure 4. CO2 emissions from various industries of public buildings in 2003-2012.

Figure 5. CO2 emissions percentages from various industry of public buildings in 2003-2012.

4.2. The Measurement of CO2 Emissions from Bottom-Up in Buildings

4.2.1. CO2 Emissions of Urban Residence Except for Central Heating

Table 5-8 demonstrate CO2 emissions of urban residence except for central heating respectively, including cooling, household appliance, domestic hot water and cooking. Results show that CO2 emissions in urban cooling and household appliance electricity, keep decreasing over a decade. Both decline rate reach the highest at 22.14% and 23.33%. However, domestic hot water and cooking keep increasing at an annual growth rate at 6.42% and 6.12% respectively.

Table 5. Urban cooling energy consumption and CO2 emissions in 2003-2012.

Year Air-conditioning energy consumption (MWh) CO2 emissions (104 tons)
2003 494394.900 49.014
2004 442064.700 43.826
2005 413951.966 41.039
2006 481367.374 47.723
2007 515421.709 51.099
2008 545687.863 54.099
2009 431984.383 42.827
2010 336300.914 33.341
2011 380700.000 37.743
2012 334568.000 33.169

Table 6. Urban household appliance electricity consumption and CO2 emissions in 2003-2012.

Year TV energy consumption (MWh) Washing machine energy consumption(MWh) Refrigerator energy consumption (MWh) Total energy consumption of domestic appliance (MWh) CO2 emissions (104tons)
2003 136384.800 51144.300 315.896 187844.996 18.623
2004 126304.200 45928.800 300.701 172533.701 17.105
2005 123680.770 38889.796 297.885 162868.452 16.147
2006 119215.838 36032.178 286.667 155534.683 15.420
2007 116447.127 35634.093 277.714 152358.935 15.105
2008 105175.219 35457.301 294.105 140926.625 13.971
2009 105462.854 34487.642 289.070 140239.566 13.903
2010 81029.024 26265.047 220.149 107514.221 10.659
2011 95175.000 25380.000 258.833 120813.833 11.977
2012 83642.000 19302.000 238.664 103182.664 10.230

Table 7. Urban domestic hot water energy consumption and CO2 emissions in 2003-2012.

Year People Per capital heating demand Domestic hot water energy consumption CO2 emissions
(persons) (kgce/a) (tons of standard coal ) (tons)
2003 19950000 1.3 25935.000 67949.700
2004 23870000 1.3 31031.000 81301.220
2005 25820000 1.3 33566.000 87942.920
2006 26990000 1.3 35087.000 91927.940
2007 27950000 1.3 36335.000 95197.700
2008 29280000 1.3 38064.000 99727.680
2009 30770000 1.3 40001.000 104802.620
2010 32010000 1.3 41613.000 109026.060
2011 33020000 1.3 42926.000 112466.120
2012 33870000 1.3 44031.000 115361.220

Table 8. Urban cooking energy consumption and CO2 emissions in 2003-2012.

Year People Per capital heating demand Cooking energy consumption CO2 emissions
(persons) (kgce/a) (tons of standard coal ) (tons)
2003 19950000 4.5 89775 235210.5
2004 23870000 4.5 107415 281427.3
2005 25820000 4.5 116190 304417.8
2006 26990000 4.5 121455 318212.1
2007 27950000 4.5 125775 329530.5
2008 29280000 4.5 131760 345211.2
2009 30770000 4.5 138465 362778.3
2010 32010000 4.5 144045 377397.9
2011 33020000 4.5 148590 389305.8
2012 33870000 4.5 152415 399327.3

4.2.2. CO2 Emissions of Rural Residence Except for Central Heating

Table 9-12 demonstrate CO2 emissions of rural residence except for central heating respectively, including cooling, household appliance, domestic hot water and cooking. Findings demonstrate that, these four parts show a decreasing trend in recent years, out of which, rural cooling has the largest annual decreasing rate at 1.04% and cooking decreases slowly at 1.59%.

 

Table 9. Rural cooling energy consumption and CO2 emissions in 2003-2012.

Year Air-conditioning energy consumption (MWh) CO2 emissions (104 tons)
2003 1248624.000 123.789
2004 1114267.000 110.468
2005 1002977.537 99.435
2006 1086830.049 107.748
2007 1172286.292 116.220
2008 1282680.891 127.165
2009 1029939.359 102.108
2010 998347.325 98.976
2011 922140.000 91.421
2012 804544.000 79.762

 

Table 10. Rural household appliance electricity consumption and CO2 emissions in 2003-2012.

Year TV energy consumption (MWh) Washing machine energy consumption(MWh) Refrigerator energy consumption (MWh) Total energy consumption of domestic appliance (MWh) CO2 emissions (104 tons)
2003 344448.00 129168.00 797.81 474413.81 47.033
2004 318362.00 115768.00 757.95 434887.95 43.115
2005 299670.12 94227.34 721.76 394619.21 39.123
2006 269165.22 81353.36 647.24 351165.82 34.815
2007 264849.87 81046.95 631.64 346528.46 34.355
2008 247222.37 83345.09 691.32 331258.77 32.84
2009 251445.07 82225.61 689.20 334359.89 33.15
2010 240543.83 77970.77 653.54 319168.13 31.64
2011 230535.00 61476.00 626.95 292637.95 29.01
2012 201136.00 46416.00 573.92 248125.92 24.60

Table 11. Rural domestic hot water energy consumption and CO2 emissions in 2003-2012.

Year People Per capital heating demand Domestic hot water energy consumption CO2 emissions
(persons) (kgce/a) (tons of standard coal ) (tons)
2003 46010000 1.3 59813.000 156710.060
2004 43670000 1.3 56771.000 148740.020
2005 42690000 1.3 55497.000 145402.140
2006 41990000 1.3 54587.000 143017.940
2007 41480000 1.3 53924.000 141280.880
2008 40610000 1.3 52793.000 138317.660
2009 39570000 1.3 51441.000 134775.420
2010 39930000 1.3 51909.000 136001.580
2011 39390000 1.3 51207.000 134162.340
2012 39760000 1.3 51688.000 135422.560

Table 12. Rural cooking energy consumption and CO2 emissions in 2003-2012.

Year People Per capital heating demand Cooking energy consumption CO2 emissions
(persons) (kgce/a) (tons of standard coal ) (tons)
2003 46010000 4.5 207045.000 542457.900
2004 43670000 4.5 196515.000 514869.300
2005 42690000 4.5 192105.000 503315.100
2006 41990000 4.5 188955.000 495062.100
2007 41480000 4.5 186660.000 489049.200
2008 40610000 4.5 182745.000 478791.900
2009 39570000 4.5 178065.000 466530.300
2010 39930000 4.5 179685.000 470774.700
2011 39390000 4.5 177255.000 464408.100
2012 39760000 4.5 178920.000 468770.400

4.2.3. CO2 Emissions of Public Buildings Except for Central Heating

Table 13 shows the construction areas of various public buildings. In addition, Table 14 illustrates energy consumption of various public buildings. As for this sector, CO2 emissions keep an upward trend.

Table 13. Construction areas of various public buildings.

  Operational Area of Catering Services (sq. m) Operational Area of hotels (sq.m) Floor Space of Public Buildings (sq.m)
2003 278000 371000 249000
2004 299000 418000 251100
2005 310000 489000 259600
2006 311000 627000 260300
2007 411000 718000 265600
2008 543000 974000 267000
2009 654000 1222000 256500
2010 774000 974000 249000
2011 1062000 1374000 304000
2012 1209000 1614000 323000

Note: reference to Hebei Statistic Yearbook.

Table 14. Energy Consumption of various public buildings.

  Operational Area of Catering Services (MWh) Operational Area of hotels (MWh) Floor Space of Public Buildings (MWh)
2003 54210 72345 48555.0
2004 58305 81510 48964.5
2005 60450 95355 50622.0
2006 60645 122265 50758.5
2007 80145 140010 51792.0
2008 105885 189930 52065.0
2009 127530 238290 50017.5
2010 150930 189930 48555.0
2011 207090 267930 59280.0
2012 235755 314730 62985.0

5. Conclusion and Implications

Derived from energy efficiency and measurement from top-down, the increasing rate of CO2 emissions in public buildings ranks the first, while total CO2 emissions in urban and rural residence keeps a huge base value in the decade. Based on the measurement from bottom-up, CO2 emissions in the service demand of cooling and cooking involved in technique combination, shows a huge growth potential.

Firstly, utilization of low-carbon material and low-carbon buildings technology should be promoted, including exterior energy-saving technology, energy-saving windows and doors, energy-saving roof, development of new energy as well as heating, refrigeration and lighting technology. Secondly, national policy support and supervision should be payed huge attention. Development of low-carbon buildings needs various energy-saving materials and technology as well as relevant policy support. China’s energy conservation in buildings is backward, which is not merely technical problems, but also governmental supervision, industrial operation and public mind. Thirdly, low-carbon buildings concept popularizing education and professional education is significant. Meanwhile, courses are also necessary to teach low-carbon buildings technology in related majors such as architecture, civil engineering, energy, management.

Acknowledgment

This work is supported by the Fundamental Research Funds for the Central Universities (No. 12ZX12).


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