Influence of envelope insulation materials on building energy consumption

Abstract

In this paper, the influence of different external wall insulation materials on the energy consumption of a newly built apartment in Germany is investigated. Three types of insulation materials commonly used in Germany including mineral fiber, polyurethane, and vacuum insulation panel are chosen for the case studies. An energy analysis model is established to clarify the primary energy use for production of the insulation materials and for building space heating. The calculation results show that the energy consumption for insulation material production increases with the insulation thickness, whereas the energy use for space heating decreases with the insulation thickness. Thus, there exists an optimum thickness to get the lowest total energy consumption for each kind of insulation material. The ascending order of the total energy consumption of the three materials is mineral fiber, polyurethane, and vacuum insulation panel. However, the optimum insulation thicknesses for the three insulation materials show a verse order at a certain heat transfer coefficient of the base envelope. The energy payback time (EPT) is proposed to calculate the payback time of the primary energy use for insulation material production. Mineral fiber has the shortest time, followed by polyurethane and vacuum insulation panel. The EPTS is 10, 19 and 21 years, respectively when the heat transfer coefficient of the base envelope is 0.2 W/(m²·K). In addition, the simulated results show that the theoretical value and the simulated value are basically identical.

Graphical abstract

Keywords

building envelope / insulation materials / energy consumption / payback time

1 Introduction

The energy cost on building is pretty high in the world. The global environmental deterioration has attracted the attention of both the local nations and international societies. In the European Union, the construction and building sector is responsible for about 40% of the overall environmental burden. Most European governments have introduced new policy instruments, such as the European Community’s energy performance directive for buildings (EPBD), in order to reduce the negative impacts of the building sector [1]. New requirements have been proposed for newly-built or refurbished buildings as the interaction of society and environment is understood in depth.

A large share of energy consumption and carbon dioxide emissions in the building sector arise from building operation and building material production, especially building envelope structural and insulation material production. There are some methods available to evaluate the environmental impacts of materials and components. Life cycle assessment (LCA) is widely used because it can treat the framework, impact assessment and data quality integrally [2]. Currently, many researchers are interested in investigating the building life cycle energy consumption and environmental impact during the extraction, processing and transportation of raw materials, and the operation of building. Gu et al. [3] developed a life cycle assessment framework to evaluate building energy conservation and the environment impact of buildings in China. Robin et al. [4] proposed a life cycle energy analysis model to analyze the house energy consumption in Australia. Carol [5] studied the real efficiency of walls with high thickness insulation materials in Italy using the methodology of environmental balance. It was found that there was a minimal value above which it was unworthy to increase the thickness of wall components to lower energy consumption. Roger et al. [6] presented some theoretical issues associated with life-cycle energy analysis and applied them to a residential building. Gu et al. [7] developed a life cycle assessment framework to evaluate building energy conservation and environment impact in Beijing, China. The model for thickness evaluation of economical insulation layer of the external wall was proposed in Xi’an, China [8].

According to the principles and frame work of LCA described in ISO 14040 and the policies and resources in China, an assessment method was established to model the target system, considering both energy consumption and environment impact [9]. Zheng et al. [10] proposed the extenics theory and life cycle assessment to evaluate the building energy conservation. Tarantini et al. [11] applied LCA to wood windows showing how it supports the environmental criteria definition. Malmqvist et al. [12] adopted a systematic approach to guide the life cycle process and clarify key issues, e.g. the choice of assessment tool, definition of system boundaries, options for simplifying the process, etc. Tsai et al. [13] adopted LCA to assess CO₂ emission costs, and applied a mathematical programming approach to maximize profits for construction companies with limited resources. Zabalza et al. [14] presented the LCA application in buildings to compare the most commonly used materials with some new eco-materials. Huberman and Pearlmutter [15] analyzed both embodied and operational energy consumption in a climatically responsive building, and compared its actual material composition with a number of possible alternatives. Ardenteet al. [16] adopted LCA on a kenaf-fiber insulation board according to the international standards of the ISO 14040 series. Blengini et al. [17] conducted a detailed LCA on a low energy family house in Northern Italy. The shell-embedded materials represented the highest relative contribution to its energy consumption. Ramesh et al. [18] found that operating and embodied phases of energy use were significant contributors to the building’s life cycle energy demand.

This paper describes a simplified approach to investigate the embodied energy of three kinds of building insulation materials and the space heating energy use in a lifetime. The total energy consumption is calculated and compared. Moreover, the optimum thickness of the insulation and the payback time are also studied.

2 Frame work of this study

The LCA methodology is based on ISO 14040 and consists of four steps: defining the goal and scope, creating the life-cycle inventory, assessing the impact, and interpreting the results [19]. This paper follows the LCA methodology to study the impact of building insulation materials widely used in Germany on the energy consumption caused by the heat losses through the building envelope. Three types of insulation materials, i.e., mineral fiber, polyurethane, and vacuum insulation panel are chosen as the research objects. The properties and production energy demand per unit mass of the three chosen insulation materials come from the previous researches in Germany [20], as shown in Table 1. The lifetime of the building insulation materials is assumed to be 30 years. A unit area of envelope is chosen as the functional unit in order to determine the energy consumption of insulation material production and the space heating energy use.

3 Calculation model

3.1 Characteristic and properties of the materials

Polyurethane is a kind of macromolecular compounds, which contains repeated carbamate groups on its main chain. The heat resistance is between –20 degrees and 120 degrees and it is pollution-free and non-toxic tasteless. It has a long service life, and therefore, it can reduce the cost.

The mineral fiber is obtained from the fibrous structure of the mineral rock fiber, containing all kinds of oxides, such as silica, alumina, magnesia.

Vacuum insulation panel is one of the vacuum thermal insulation materials, combining with the filling materials and vacuum protection surface layer. It can effectively avoid the heat transfer caused by air convection, thus its thermal conductivity can be greatly reduced. It is currently the most advanced and efficient heat preservation material in the world.

The properties and production energy demand of the three kinds of materials are listed in Table 1.

3.2 Total primary energy consumption

In this paper, the total energy consumption comprises two parts, the energy compensating the heat transfer losses of the building envelope (i.e., the energy for space heating), and the energy for producing the insulation materials.

(1)E_{\mathrm{tot}}=E_{\mathrm{t}}+E_{\mathrm{in}},

where E_tot is the total primary energy, kWh/m²; E_t is the primary energy for space heating, kWh/m²; and E_in is the primary energy for producing the insulation materials, kWh/m².

The annual heat loss is assumed to be constant during the lifetime of a building. Therefore, the entire energy demand for space heating can be calculated by Eq. (2).

(2)E_{\mathrm{t}}={\displaystyle \frac{k\times G_{\mathrm{t}}\times \mathrm{24}}{{\eta }_{\mathrm{t}}\times \mathrm{1000}}}\times N,

where k is the overall heat transfer coefficient of the building envelope as expressed in Eq. (3), W/(m²·K); G_t is the annual heating days, K/d; N is the lifetime of the insulation materials; and η_t is the efficiency of the heating system.

(3)k={\displaystyle \frac{\mathrm{1}}{{\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{i}}}}+{\displaystyle \frac{\mathrm{1}}{k_{\mathrm{bw}}}}+{\displaystyle \frac{{\delta }_{\mathrm{in}}}{{\lambda }_{\mathrm{in}}}}+{\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{o}}}}}},

where α_i is the heat transfer coefficient of the internal surface convection, W/(m²·K); α_o is the heat transfer coefficient of the external surface convection, W/(m²·K); k_bw is the overall heat transfer coefficient of the base envelope without insulation material, W/(m²·K); δ_in is the thickness of the insulation layer, m; and λ_in is the thermal conductivity of the insulation material, W/(m·K).

For an envelope surface of one square meter, the total production energy consumption of insulation material can be calculated by using Eq. (4).

(4)E_{\mathrm{in}}={\displaystyle \frac{{\rho }_{\mathrm{in}}\times {\delta }_{\mathrm{in}}\times P{E}_{\mathrm{in}}\times \mathrm{1000}}{\mathrm{3600}}},

where ρ_in is the density of the insulation material, kg/m³; PE_in is the production energy demand per unit mass of the insulation material, MJ/kg.

According to Eq. (1), the total primary energy consumption can be rewritten as

(5)E_{\mathrm{tot}}={\displaystyle \frac{G_{\mathrm{t}}\times \mathrm{24}\times N}{\mathrm{1000}\times {\eta }_{\mathrm{t}}\times \left({\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{i}}}}+{\displaystyle \frac{\mathrm{1}}{k_{\mathrm{bw}}}}+{\displaystyle \frac{{\delta }_{\mathrm{in}}}{{\lambda }_{\mathrm{in}}}}+{\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{o}}}}\right)}}+{\displaystyle \frac{{\rho }_{\mathrm{in}}\times {\delta }_{\mathrm{in}}\times P{E}_{\mathrm{in}}\times \mathrm{1000}}{\mathrm{3600}}}.

3.3 Optimum thickness of insulation layer

Obviously, the primary energy for production of the insulation materials will increase for the thicker insulation. However, this may reduce the energy use for space heating. Thus, the total primary energy consumption will change with the insulation thickness. Once it takes the minimum value, the corresponding insulation thickness is defined as its optimum thickness. Under the optimum thickness of the insulation layer, the partial derivative of E_tot in Eq. (5) with respect to δ_in should equal zero, i.e. \partial E_{\mathrm{tot}}/\partial {\delta }_{\mathrm{in}}=\mathrm{0}. So the optimum thickness of the insulation layer can be obtained by using Eq. (6).

(6){\delta }_{\mathrm{opt}}=\sqrt{{\displaystyle \frac{\mathrm{3.6}\times G_{\mathrm{t}}\times \mathrm{24}\times N\times {\lambda }_{\mathrm{in}}}{\mathrm{1000}\times {\eta }_{\mathrm{t}}\times {\rho }_{\mathrm{in}}\times P{E}_{\mathrm{in}}}}}-{\lambda }_{\mathrm{in}}\times \left({\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{i}}}}+{\displaystyle \frac{\mathrm{1}}{k_{\mathrm{bw}}}}+{\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{o}}}}\right),

where δ_opt is the optimum thickness of the insulation layer, m.

In addition, the second order derivative of E_tot with respect to δ_in is given by Eq. (7).

(7){\displaystyle \frac{{\partial }^{\mathrm{2}}{{\displaystyle E}}_{\mathrm{t}\mathrm{o}\mathrm{t}}}{\partial {{\displaystyle \delta }}_{\mathrm{i}\mathrm{n}}^{\mathrm{2}}}}={\displaystyle \frac{\mathrm{2}\times {{\displaystyle G}}_{\mathrm{t}}\times \mathrm{24}\times N\times {{\displaystyle \lambda }}_{\mathrm{i}\mathrm{n}}}{\mathrm{1000}\times {{\displaystyle \eta }}_{\mathrm{t}}{{\displaystyle \left[{{\displaystyle \lambda }}_{\mathrm{i}\mathrm{n}}\times \left({\displaystyle \frac{\mathrm{1}}{{{\displaystyle \alpha }}_{\mathrm{i}}}}+{\displaystyle \frac{\mathrm{1}}{{{\displaystyle k}}_{\mathrm{b}\mathrm{w}}}}+{\displaystyle \frac{\mathrm{1}}{{{\displaystyle \alpha }}_{\mathrm{o}}}}\right)+{{\displaystyle \delta }}_{\mathrm{i}\mathrm{n}}\right]}}^{\mathrm{3}}}}.

From Eq. (7), it can be seen that the value of the second order derivative is greater than zero. Therefore, the optimum thickness of the insulation layer in Eq. (6) is the minimum value.

3.4 Energy payback time(EPT)

In fact, increasing the use of insulation in the external envelope systems of buildings will reduce the space heating demand. However, this may increase the building insulation material production energy. Therefore, it will take some years to pay back the cost by the energy savings from the reduced space heating energy use.

The annual heat loss through the base envelope without insulation material is given as

(8)Q_{\mathrm{tb}}={\displaystyle \frac{G_{\mathrm{t}}\times \mathrm{24}}{\mathrm{1000}\times {\eta }_{\mathrm{t}}\times \left({\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{i}}}}+{\displaystyle \frac{\mathrm{1}}{k_{\mathrm{bw}}}}+{\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{o}}}}\right)}},

where Q_tb is the annual heat loss through the base envelope, kWh/(m²·a).

The annual heat loss through the envelope with insulation material can be calculated by using Eq. (9).

(9)Q_{\mathrm{tin}}={\displaystyle \frac{G_{\mathrm{t}}\times \mathrm{24}}{\mathrm{1000}\times {\eta }_{\mathrm{t}}\times \left({\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{i}}}}+{\displaystyle \frac{\mathrm{1}}{k_{\mathrm{bw}}}}+{\displaystyle \frac{{\delta }_{\mathrm{in}}}{{\lambda }_{\mathrm{in}}}}+{\displaystyle \frac{\mathrm{1}}{{\alpha }_{\mathrm{o}}}}\right)}},

where Q_tin is the annual heat loss through the envelope with insulation material, kWh/(m²·a).

The energy payback time (EPT) is defined as the ratio of the production energy consumption of the insulation material to the annual reduced heat loss due to addition of the insulation, as presented in Eq. (10).

(10)\mathrm{EPT}={\displaystyle \frac{E_{\mathrm{in}}}{Q_{\mathrm{tb}}-Q_{\mathrm{tin}}}},

where EPT is the energy payback time, year.

3.5 Assumptions

To simplify the simulation, it is assumed that the base envelope k_bw is from 0.2 to 1.0 W/(m²·K); G_t is the heating days in Essen, Germany, G_t=2273Kd; δ_in is from 0 to 0.5 m; η_t is given as 90%; N is 30 years; and 1/α_i and 1/α_o are 0.11 (m²·K)/W and 0.04 (m²·K)/W.

4 Results and discussion

4.1 Energy consumption of three insulation materials

The overall heat transfer coefficient of the base envelope k_{\mathrm{bw}}is assumed to be 1.0 W/(m²·K) and the energy consumptions of mineral fiber, polyurethane and vacuum insulation panel over 30 years under different insulation thickness are calculated, as depicted in Figs. 1 to 3, respectively. It can be observed that all the production energy consumptions arise linearly with the insulation thickness, and the vacuum insulation panel shows the highest value, whereas the heat losses of the envelope show an opposite trend. Moreover, the heat losses are very great without insulation materials. Once the insulation material is applied, the heat losses drop abruptly with the insulation thickness. The total energy consumption first decreases to a minimal value at a certain thickness and then increases with the thickness. Hence, there exists an optimum insulation thickness corresponding to the lowest value of the total energy consumption.

4.2 Comparison of total energy consumption

Figure 4 plots the total energy consumptions for the three insulation materials as k_bw is 1.0 W/(m²·K). Obviously, the total energy consumption for the vacuum insulation panel is higher than that for the other two materials. With the increase of the insulation thickness, the gap increases. The total energy consumption of mineral fiber is the lowest while that of polyurethane is slightly higher. The total energy consumption for the three insulation materials first decreases and then increases with the increase in insulation thickness. Each material has the corresponding optimum insulation thicknesses which leads to different total energy consumptions.

4.3 Optimum thickness of insulation

If the overall heat transfer coefficient of the base envelope k_bw varies, the optimum thickness of the insulation varies accordingly, as shown in Fig. 5. The optimum insulation thicknesses for the three materials increase slightly with the increase in k_bw. It also can be found that the optimum thickness of the mineral fiber ranging from 33 to 47 cm is the largest, while the optimum thickness of the vacuum insulation panel, from 1 to 3 cm, is the smallest. It is attributed to the different production energy demands and properties of the materials, such as the density and the thermal conductivity, as listed in Table 1.

4.4 Reduced heat losses

The curves of the reduced heat losses versus for each material, which is calculated at the optimum insulation thickness, are presented in Fig. 6. It can be seen that the reduced heat losses rise linearly with increasing the overall heat transfer coefficient of the base envelope. Besides, the reduced heat loss of mineral fiber is larger than that of the other materials. The reduced heat loss of the polyurethane is almost equivalent to that of the vacuum insulation panel.

4.5 Energy payback time (EPT)

The curves of energy payback time versus k_bw for each insulation material, which are calculated at the optimum insulation thickness, are plotted in Fig. 7. It is shown that when the heat transfer coefficient of the base envelope is reduced, the energy payback time increases quickly. For example, as k_bw is 1.0 W/(m²·K), the EPTs for vacuum insulation panel, polyurethane and mineral fiber are 5, 4 and 2 years, respectively. It can be seen that mineral fiber has the shortest EPT, followed by polyurethane and vacuum insulation panel. As heat transfer coefficient of the base envelope is 0.2 W/(m²·K), the EPT is 10, 19 and 21 years, respectively.

5 Case study

The case study is based on an existing building with acoustic tile and Conc HW 140lb external wall. The external wall insulation material was varied from polyurethane to vacuum insulation panel or mineral fiber with a thickness of 10 to 50 mm to verify the correctness of the theoretical calculation.

5.1 Building descriptions

The building studied is a residential one with armoured concrete frame, in China-Singapore project in the Eco-city in Tianjin, China. The building has 20 floors and a total heated floor area of 70570.36 m², with city heating net. Figure 8 demonstrates the simulated photograph of the building.

5.2 Simulation results

Assuming that the indoor temperature is 22°C for the living area and 18°C for common area, the equest software [9] was used to calculate the space heating energy of the building.

The total energy consumption of the building studied of the above theoretical calculated value with the simulated value for polyurethane and vacuum insulation panel of over 30 years at different insulation thicknesses is compared in Figs. 9 and 10, respectively.

Figure 9 displays the change of the total energy consumption of the theoretical and the simulated value for polyurethane with the insulation thickness. It can be seen that the theoretical value is greater than that of the simulated value in all range of the insulation thickness. It can be observed that there is a minimum value in the theoretical result, but the simulated value has been increased. The reason for this is that the result of the theoretical calculation is relatively accurate in differential operation. The thickness of the simulation value is discontinuous, which may miss the minimum point.

The comparison of the simulated and the theoretical value is shown in Fig. 10. It can be seen that the two values are in perfect agreement, which verifies the correctness of the theoretical calculation by the simulation.

6 Conclusions

In this paper, an energy analysis model was established to investigate the effect of three types of insulation materials on the thermal performance and the total energy consumption of buildings. Due to different properties and production energy demands per unit mass for different materials, the total energy consumption is not the same. Vacuum insulation panel is a high-density and energy-intensive material, and its total energy consumption is the largest of the three materials, while the opposite is true of mineral fiber. There is an optimum insulation thickness for each material to lead to the lowest total energy consumption. Vacuum insulation panel has the smallest optimum insulation thickness and mineral fiber has the largest. The energy payback time mainly depends on the heat transfer coefficients of the base envelope, and the vacuum insulation panel corresponds to the longest payback time.

In addition, the equest software was used to simulate a building to verify the correctness of the theoretical calculation. The results show that the theoretical value and the simulated value are basically identical.

Thus, the total energy consumption and the envelope structure should be considered comprehensively in choosing insulation materials; otherwise it will take a very long time to pay back the production energy consumption of the materials.

Furthermore, in order to ensure the sustainable development of the construction industry, the investigation of the resources consumption, environmental impact and economic investment of the materials should be conducted comprehensively and simultaneously.

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