Previous Article in Journal
Study on Corporate Social Responsibility (CSR): Focus on Tax Avoidance and Financial Ratio Analysis

Article

# Optimum Insulation Thickness for Building Exterior Walls in 32 Regions of China to Save Energy and Reduce CO2 Emissions

by
Department of Housing and Environmental Design, Graduate School of Human Life Science, Osaka City University, Osaka 5588585, Japan
*
Author to whom correspondence should be addressed.
Sustainability 2017, 9(10), 1711; https://doi.org/10.3390/su9101711
Received: 8 September 2017 / Revised: 19 September 2017 / Accepted: 22 September 2017 / Published: 24 September 2017

## Abstract

#### 2.4. Determination of Optimum Insulation Thickness

The minimum CT is taken as the point when the derivative of the cost as a function of insulation thickness (8) reaches zero, in the following Equations (11) and (12) [27],
$d C T d x = d d x [ P W F ( C H ⋅ m H + C C ⋅ m C ) + C i n s ⋅ x ]$
and
$d C T d x = 0$
The OIT can be also derived using the following Equation (13) [28],
$O I T = 86.4 ⋅ H D D 18.0 ⋅ C H ⋅ P W F ⋅ k H H ⋅ C i n s ⋅ η H + 86.4 ⋅ C D D 28.0 ⋅ C C ⋅ P W F ⋅ k H C ⋅ C i n s ⋅ η C − R w t ⋅ k$

#### 2.5. Energy Cost Saving Analysis

The potential annual energy cost saving per unit area of building exterior walls can be derived by subtracting the annual total energy cost per unit area of building exterior walls for noninsulated walls and the annual total cost per unit area of building exterior walls for insulated walls. The relationship is shown as the following Equation (14),
$E c s = ( C T ) n i n s − ( C T ) i n s$

#### 3.5. Potential Annual CO2 Emissions

The potential annual CO2 emission per unit area of building exterior walls, mco2, is derived from the above Equations (15)–(18). The curves of mco2 versus the insulation thickness for example regions of Tibet, Shanghai, Yunnan and Guangdong are shown in Figure 8.
Figure 8 shows that Tibet has the largest reduction of mco2 of about 53 kg/m2-yr when the insulation thickness increases up to the OIT value of 135 mm, followed by Shanghai (CO2 emission reduction is about 35 kg/m2-yr when the insulation thickness increases up to the OIT value of 78 mm) and Yunnan (CO2 emission reduction is about 24 kg/m2-yr when the insulation thickness increases up to the OIT value of 63 mm). Guangdong has the smallest reduction of mco2 of about 5 kg/m2-yr when the insulation thickness increases up to the OIT value of 22 mm.
If the OIT for building exterior walls is applied, the reduction of mco2 for 32 regions of China are predicted and detailed in Table 2.
It is seen that the mco2 decreases by increasing the insulation thickness of exterior walls. When the OIT for exterior walls is used, the average mco2 of 32 regions of China can potentially be reduced by about 27 kg/m2-yr (63%).
In addition, we can see that when the region is much colder (such as Tibet), the reduction rate of mco2 as the insulation thickness increases is much larger. Thus, in order to greatly reduce mco2 in China, it is considered that it is more effective to implement the thermal insulation technology on the exterior walls of buildings in Severe Cold and Hot Summer & Cold Winter climatic zones rather than the other climatic zones of China.

## 4. Conclusions and Future Work

For the purpose of contributing to the thermal insulation design of building exterior walls for energy cost savings and CO2 emission reduction in China, this study proposed the OIT of exterior walls for 32 regions of China using more recent data via the DD method and LCCA over a hypothetical lifetime of 10 years, without considering the influence of windows and external solar gains. In addition, the impact of the OIT on the annual total energy cost and annual CO2 emissions per unit area of building exterior walls were also implemented in this study.
The findings indicate the thermal insulation of exterior walls is more effective in Severe Cold and Hot Summer & Cold Winter climatic zones of China for both total energy cost saving and CO2 emissions reduction per unit area of the building exterior walls, however it is the opposite in Hot Summer & Warm Winter climatic zones of China. It is predicted that the average annual total energy cost per unit area of building exterior walls can potentially be decreased by about $5/m2-yr (40%) and the average annual CO2 emissions per unit area of building exterior walls can potentially be reduced by about 27 kg/m2-yr (63%) for the 32 regions of China if the OIT is adopted. For the future research, it will focus on the impact of the other parameters, i.e., windows of exterior walls, solar gains of exterior walls, different energy sources and a greater variety of wall construction and materials, etc. on the OIT design, total energy cost and CO2 emissions in different climatic zones of China. Furthermore, the cost of installing thermal insulation and labor will be considered when calculating the OIT of exterior walls. Finally, the potential for the possibility of introducing solar energy as a renewable energy to substitute for coal and natural gas in different climatic zones of China will be considered in future as it will largely affect the OIT design, total energy cost and CO2 emissions. ## Acknowledgments The authors are sincerely grateful to the China Meteorological Data Service Center (CMDC) for supporting the meteorological database in this study. ## Author Contributions For research articles with three authors, Jihui Yuan (100%) collected the meteorological database for analysis; Jihui Yuan (80%), Craig Farnham (10%) and Kazuo Emura (10%) implemented the calculation of optimum insulation thickness design for China regions; Jihui Yuan wrote the paper; Craig Farnham (a native English speaker) checked the English of paper. ## Conflicts of Interest The authors declare no conflicts of interest. ## References 1. Dombaycı, Ö.A. Investigation of the Effect of Thermal Insulation for a Model House in Cold Regions: A Case Study of Turkey. Environ. Progress Sustain. Energy 2013, 33, 527–537. [Google Scholar] [CrossRef] 2. Mardookhy, M.; Sawhney, R.; Ji, S.; Zhu, X.; Zhou, W. A Study of Energy Efficiency in Residential Buildings in Knoxville, Tennessee. J. Clean. Prod. 2014, 85, 241–249. [Google Scholar] [CrossRef] 3. Baniassadi, A.; Sajadi, B.; Amidpour, M.; Noori, N. Economic optimization of PCM and insulation layer thickness in residential buildings. Sustain. Energy Technol. Assess. 2016, 14, 92–99. [Google Scholar] [CrossRef] 4. Qin, Y.; Zhang, M.; Hiller, J.E. Theoretical and experimental studies on the daily accumulative heat gain from cool roofs. Energy 2017, 129, 138–147. [Google Scholar] [CrossRef] 5. Yuan, J.; Farnham, C.; Emura, K.; Alam, M.A. Proposal for optimum combination of reflectivity and insulation thickness of building external walls for annual thermal load in Japan. Build. Environ. 2016, 103, 228–237. [Google Scholar] [CrossRef] 6. Ozel, M. Effect of wall orientation on the optimum insulation thickness by using a dynamic method. Appl. Energy 2011, 88, 2429–2435. [Google Scholar] [CrossRef] 7. Sisman, N.; Kahya, E.; Aras, N.; Aras, H. Determination of optimum insulation thicknesses of the external walls and roof (ceiling) for Turkey’s different degree-day regions. Energy Policy 2007, 35, 5151–5155. [Google Scholar] [CrossRef] 8. Yu, J.; Yang, C.; Tian, L.; Liao, D. A study on optimum insulation thicknesses of external walls in hot summer and cold winter zone of China. Appl. Energy 2009, 86, 2520–2529. [Google Scholar] [CrossRef] 9. Dombaycı, Ö.A.; Gölcü, M.; Pancar, Y. Optimization of insulation thickness for external walls using different energy-sources. Appl. Energy 2006, 83, 921–928. [Google Scholar] [CrossRef] 10. Özkan, D.B.; Onan, C. Optimization of insulation thickness for different glazing areas in buildings for various climatic regions in Turkey. Appl. Energy 2011, 88, 1331–1342. [Google Scholar] [CrossRef] 11. Kurekci, N.A. Determination of optimum insulation thickness for building walls by using heating and cooling degree-day values of all Turkey’s provincial centers. Energy Build. 2016, 118, 197–213. [Google Scholar] [CrossRef] 12. Dombayci, Ö.A.; Ozturk, H.K.; Atalay, Ö.; Acar, Ş.G.; Ulu, E.Y. The Impact of Optimum Insulation Thickness of External Walls to Energy Saving and Emissions of CO2 and SO2 for Turkey Different Climate Regions. Energy Power Eng. 2016, 8, 327–348. [Google Scholar] [CrossRef] 13. Uçar, A.; Balo, F. Effect of fuel type on the optimum thickness of selected insulation materials for the four different climatic regions of Turkey. Appl. Energy 2009, 86, 730–736. [Google Scholar] [CrossRef] 14. Hwaish, A.N.A. Impact of heat exchange on building envelope in the hot climates. Int. J. Emerg. Technol. Adv. Eng. 2015, 5, 47–57. [Google Scholar] 15. Wati, E.; Meukam, P.; Nematchoua, M.K. Influence of external shading on optimum insulation thickness of building walls in a tropical region. Appl. Therm. Eng. 2015, 90, 754–762. [Google Scholar] [CrossRef] 16. Lee, M.J.; Lee, K.G.; Seo, W.D. Analyses on performances of heat and multilayer reflection insulators. J. Cent. South Univ. 2012, 19, 1645–1656. [Google Scholar] [CrossRef] 17. Kossecka, E.; Kosny, J. Influence of insulation configuration on heating and cooling loads in a continuously used building. Energy Build. 2002, 34, 321–331. [Google Scholar] [CrossRef] 18. Ozel, M. The influence of exterior surface solar absorptivity on thermal characteristics and optimum insulation thickness. Renew. Energy 2012, 39, 347–355. [Google Scholar] [CrossRef] 19. Granzotto, N.; Bettarello, F.; Ferluga, A.; Marsich, L.; Schmid, C.; Fausti, P.; Caniato, M. Energy and acoustic performances of windows and their correlation. Energy Build. 2017, 136, 189–198. [Google Scholar] [CrossRef] 20. Baldinelli, G.; Asdrubali, F.; Baldassarri, C.; Bianchi, F.; D’Alessandro, F.; Schiavoni, S.; Basilicata, C. Energy and environmental performance optimization of a wooden window: A holistic approach. Energy Build. 2014, 79, 114–131. [Google Scholar] [CrossRef] 21. Thalfeldt, M.; Pikas, E.; Kurnitski, J.; Voll, H. Facade design principles for nearly zero energy buildings in a cold climate. Energy Build. 2013, 67, 309–321. [Google Scholar] [CrossRef] 22. China Climate Change Info-Net (CCCIN). Global Carbon Dioxide Emissions in 2016. Available online: http://www.ccchina.gov.cn (accessed on 20 February 2017). 23. Ministry of Construction of the People’s Republic of China. Thermal Design Code of Civil Building (GB 50176─93); China Plan Publishing House: Beijing, China, 1993. (In Chinese) 24. Li, B.; Yao, R. Urbanization and its impact on building energy consumption and efficiency in China. Renew. Energy 2009, 34, 1994–1998. [Google Scholar] [CrossRef] 25. Zhu, P.; Huckemann, V.; Fisch, M.N. The optimum thickness and energy saving potential of external wall insulation in different climate zones of China. Procedia Eng. 2011, 21, 608–616. [Google Scholar] [CrossRef] 26. China Meteorological Data Service Center (CMDC). 2016. Available online: http://data.cma.cn (accessed on 21 February 2017). 27. Cengel, Y.A. Heat Transfer: A Practical Approach; McGraw-Hill: New York, NY, USA, 1998. [Google Scholar] 28. Hasan, A. Optimum insulation thickness for buildings using life cycle cost. Appl. Energy 1999, 63, 115–124. [Google Scholar] [CrossRef] 29. Dombayci, Ö.A. The environment impact of optimum insulation thickness for external walls of buildings. Build. Environ. 2007, 42, 3855–3859. [Google Scholar] [CrossRef] 30. Polyurethane Price from Alibaba Global Trade. 2017. Available online: https://www.alibaba.com/showroom/price-of-polyurethane-resin.html (accessed on 21 February 2017). 31. Natural Gas Price from energy.cngold.org. 2017. Available online: http://energy.cngold.org/tianranqi.html (accessed on 21 March 2017). 32. Coal Price from energy.cngold.org. 2017. Available online: http://www.cngold.org/meitan/ (accessed on 21 February 2017). 33. Electricity Price from State Grid Corporation of China. Available online: http://www.sgcc.com.cn/ (accessed on 21 March 2017). 34. Yildiz, A.; Gurlek, G.; Erkek, M.; Özbalta, N. Economical and Environmental Analysis of Thermal Insulation Thickness in Buildings. J. Therm. Sci. Technol. 2008, 28, 25–34. [Google Scholar] 35. China Interest Rate. 2017. Available online: http://www.tradingeconomics.com/china/interest-rate (accessed on 25 March 2017). 36. China Inflation Rate. 2017. Available online: http://www.tradingeconomics.com/china/inflation-cpi (accessed on 25 March 2017). 37. Andreola, F.; Barbieri, L.; Lancellotti, I. Valorization of tyres waste pyrolysis residue in lightweight materials. Environ. Eng. Manag. J. 2016, 15, 1907–1914. [Google Scholar] Figure 1. Five different climatic zones in China. Figure 1. Five different climatic zones in China. Figure 2. Geographic locations of selected 32 regions of China. Figure 2. Geographic locations of selected 32 regions of China. Figure 3. Cross-sectional view of two kinds of exterior wall structures; (a) for Severe Cold and Cold climatic zones and (b) for Hot Summer & Cold Winter, Temperate and Hot Summer & Warm Winter climatic zones. Figure 3. Cross-sectional view of two kinds of exterior wall structures; (a) for Severe Cold and Cold climatic zones and (b) for Hot Summer & Cold Winter, Temperate and Hot Summer & Warm Winter climatic zones. Figure 4. Distribution maps of annual HDD18.0 (a) and CDD28.0 (b) for 32 regions of China. Figure 4. Distribution maps of annual HDD18.0 (a) and CDD28.0 (b) for 32 regions of China. Figure 5. Distribution map of OIT for the whole China territory. Figure 5. Distribution map of OIT for the whole China territory. Figure 6. Annual cost (total cost, insulation cost, fuel cost) versus insulation thickness for Tibet, Shanghai, Yunnan and Guangdong. Figure 6. Annual cost (total cost, insulation cost, fuel cost) versus insulation thickness for Tibet, Shanghai, Yunnan and Guangdong. Figure 7. Annual energy cost saving versus insulation thickness for Tibet, Shanghai, Yunnan and Guangdong. Figure 7. Annual energy cost saving versus insulation thickness for Tibet, Shanghai, Yunnan and Guangdong. Figure 8. Annual CO2 emissions versus insulation thickness for Tibet, Shanghai, Yunnan and Guangdong. Figure 8. Annual CO2 emissions versus insulation thickness for Tibet, Shanghai, Yunnan and Guangdong. Table 1. Parameter value used in the calculations. Table 1. Parameter value used in the calculations. ParameterUnitValue Cost of insulation material (Cins) Expanded polyurethane (EPS) [30]$/m338
Fuel price (CH and CC)
Natural gas [31]$/m30.48 Coal [32]$/kg0.09
Electricity [33]$/kWh0.09 Fuel value (HH and HC) Natural gas [11]kJ/m348,570 Coal [11]kJ/kg25,122 Electricity [25]KJ/kWh3600 Efficiency of heating system (ηH) Natural gas [34][-]0.93 Coal [29][-]0.65 Present worth factor (PWF) Interest rate (i) [35] [-]4.35% Inflation rate (g) [36][-]2.3% N[yr]10 Table 2. Calculation results for 32 regions of China. Table 2. Calculation results for 32 regions of China. RegionsHDD18.0 [°C-day] CDD28.0 [°C-day] OIT [mm] (Optimum Rins [m2K/W]) Ecs [$/m2-yr]
mco2 Reduction
[kg/m2-yr]
Bejing3155.4075.14 (1.79)4.0720.80
Gansu2773.3067.16 (1.60)3.2517.30
Hebei2625.1063.91 (1.52)2.9415.29
Heilongjiang5121.70110.16 (2.62)8.7637.86
Henan2141.0052.62 (1.25)2.0011.40
Jilin4690.40103.15 (2.46)7.6833.59
Liaoning3975.3090.79 (2.16)5.9527.41
Inner Mongolia4230.6095.32 (2.27)6.5630.29
Ningxia3515.4082.24 (1.96)4.8724.25
Qinghai4321.1096.89 (2.31)6.7830.94
Shaanxi3220.6076.46 (1.82)4.2221.22
Shandong2641.7064.28 (1.53)2.9716.48
Shanxi3753.7086.73 (2.07)5.4325.88
Tianjin2731.5066.25 (1.58)3.1717.04
Xinjiang6085.00124.81 (2.97)11.2447.34
Tibet6786.90134.76 (3.21)13.1152.80
Anhui1775.827.389.67 (2.14)6.9143.56
Chongqing1308.53.070.12 (1.67)4.2329.32
Fujian496.62.626.30 (0.63)0.597.34
Guangdong423.218.621.86 (0.52)0.414.82
Guangxi381.623.518.94 (0.45)0.314.35
Guizhou2035.8098.28 (2.34)8.3051.61
Hainan14.147.80 (0)00
Hubei1569.157.582.67 (1.97)5.8736.99
Hunan1454.355.578.01 (1.86)5.2334.29
Jiangsu1831.520.791.54 (2.18)7.2044.92
Jiangxi1353.875.874.51 (1.77)4.7631.94
Paracel Islands31.60.50 (0)00
Shanghai1478.434.678.32 (1.86)5.2734.83
Sichuan1430.8075.24 (1.79)4.8633.69
Yunnan1150.3062.89 (1.50)3.4024.21
Zhejiang1542.445.681.24 (1.93)5.6736.35
Note: the upper 16 regions belong to Severe Cold and Cold climatic zones and the lower 16 regions belong to Hot Summer & Cold Winter, Temperate and Hot Summer & Warm Winter climatic zones; the value in the parenthesis of OIT column is the value of optimum thermal resistance of insulation.