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. 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 schools、public 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).
References