A Case Study of Air Infiltration for Highly Airtight Buildings under the Typical Meteorological Conditions of China

Abstract

Passive house standard buildings (PHSBs), characterized by exceptional airtightness, present a promising technology for attaining carbon neutrality by 2060. The level of building airtightness is closely associated with air infiltration, which significantly impacts building energy consumption. However, there has been insufficient analysis of air infiltration in highly airtight buildings across diverse climatic regions. The present study involves the numerical simulation of the air infiltration rate (AIR) in an airtight building under varying design conditions during winter and summer, followed by a comprehensive analysis of the corresponding energy demand associated with air infiltration. The simulation results indicate that the building’s AIR ranges from 125 to 423 m³/h, with an average of 189 m³/h under summer design conditions, and from 40 to 344 m³/h, with an average of 198 m³/h under winter design conditions. The statistical findings demonstrate distinct distribution patterns for AIR and energy demand across various climatic regions, exhibiting significant variations in values. The discussion emphasizes the substantial heating load associated with air infiltration, even at a building airtightness level of 0.5 h⁻¹, highlighting the necessity of considering its impact in the design of highly airtight buildings. Furthermore, it is recommended to establish specific airtightness limits for buildings in different climatic regions of China. This study offers theoretical guidance for the airtightness design of highly airtight buildings.

1. Introduction

At the UN General Assembly, President Xi of China declared that more forceful policies and measures will be adopted to make China’s carbon dioxide emissions peak by 2030 and achieve carbon neutrality by 2060 [1]. Passive house standard buildings (PHSBs), characterized by high levels of airtightness, represent an effective technology for achieving carbon neutrality by 2060 [2]. The Technical Standard for Nearly Zero Energy Buildings (NZEBs) was introduced by China in 2019 [3], specifying that the airtightness (ACH₅₀) of residential NZEBs in cold and severely cold regions should not exceed 0.6 h⁻¹, while for residential NZEBs in other climatic regions, it should not exceed 1.0 h⁻¹.

The building envelope is a typical multi-layer porous structure, and air infiltration occurs when there is a pressure difference across it. During the infiltration process, coupled heat and humidity transfer takes place between moist air and permeable envelope materials due to variations in the indoor and outdoor air temperatures and humidity levels [4]. The combined transfer of heat and humidity in this process leads to the accumulation of moisture within the building envelope, potentially resulting in condensation of moist air. Such conditions can have an impact on the physical properties and service life of building materials, as well as compromise the integrity and durability of the overall structure. A study conducted by Silberstein and Hens [5] revealed that inadequate airtightness in platform roofing leads to increased air infiltration, resulting in compromised thermal insulation performance and excessive water vapor diffusion. A study conducted by Hagentoft and Harderup [6] demonstrated that despite implementing appropriate measures to regulate the indoor air moisture content, the infiltration of air still results in excessive moisture accumulation within the building envelope, surpassing the targeted control level. In cold and severely cold regions, the infiltration process can result in water vapor condensation in indoor environments due to the significant temperature disparity between indoors and outdoors. This phenomenon alters the physical characteristics of porous building materials, leading to a decline in their thermal insulation performance as the moisture content increases [7].

Airtightness is closely linked to building air infiltration, which significantly impacts building energy consumption [8,9]. A relatively high rate of air infiltration increases the burden on the building’s heating, ventilation, and air conditioning system, leading to unnecessary energy waste. An excessively high air infiltration rate (AIR) can cause the building load to exceed the operational capacity of the HVAC system, thereby compromising the thermal comfort in indoor environments [10]. Jokisalo and Kurnitski [11] utilized a typical Helsinki house as an example to simulate and analyze the impact of building thermal inertia, airtightness, and other factors on heating energy consumption. The simulation results indicated that building airtightness has the most significant influence. The heating energy consumption increased from 4% to 21% as the ACH₅₀ gradually rose from 1 to 10 h⁻¹. The impact of airtightness on the energy consumption of the exterior doors and windows of residential buildings has also been simulated and analyzed by scholars [12,13]. The findings indicate that enhancing the airtightness level of these doors and windows can effectively reduce the heating energy consumption while still meeting air change rate requirements. Claesson and Hellstrom [14] discovered that air infiltration has an impact on the heat flow through the insulation material of the building envelope, leading to an increase in convective heat transfer between the air and the porous material, thereby enhancing the heat dissipation of the envelope.

Numerous scholars have extensively investigated the proportion of heat consumed through building air infiltration. Caffey [15] pointed out that 40% of the cooling and heating load of residential buildings is caused by air infiltration, and Persily [16] calculated that the proportion was a third. The National Institute of Standards and Technology stated that 15% of heating energy use in commercial buildings is due to air infiltration [17]. Emmerich and Persily [18] found that 13% of the heating load and 3% of the cooling load of office buildings in the United States are caused by air infiltration. Binamu [19] pointed out that 53% of the ventilation heat load of residential buildings in cold areas is caused by air infiltration. Jokisalo et al. [20] simulated the heat consumption of a single villa in a cold area, and the results showed that the heat consumption of air infiltration accounted for 30%. Perino et al. [21] simulated the cooling and heating loads of residential buildings with or without air infiltration, and the results showed that the cooling and heating loads increased by 30.5% when there was air infiltration. The results of a field test indicated that in an airport situated in a hot-summer and cold-winter climatic zone of China, the energy consumption attributed to air infiltration accounts for over 50% of the total heating supply provided by the air-conditioning system [22]. Han et al. [23] suggested that air infiltration in an office building in Michigan accounts for 15–50% of the total energy consumption for heating and cooling purposes. Brinks et al. [24] proposed that air infiltration in industrial buildings constitutes 40% of the overall heating energy demand in Germany. Meiss and Feijó-Muñoz [25] pointed out that air infiltration can contribute to up to 30% of the winter heating demand for dwellings in north-central Spain. A study conducted by Fernández-Agüera [26] revealed that infiltration accounts for 15% to 25% of the heating energy demand in typical social housing constructed prior to Spain’s earliest legislation on building airtightness. The significant impact of air infiltration on building energy consumption has also been observed in passive houses [27], commercial buildings [28], container houses [29], large-space buildings [30], and historical buildings [31]. The aforementioned research demonstrates that although the proportion of energy consumed by air infiltration varies across different types of buildings and time periods, it is evident that energy consumption resulting from air infiltration constitutes a significant component of building energy consumption.

China possesses an extensive territory encompassing five distinct climatic regions, resulting in significant variations in meteorological parameters. These parameters play a pivotal role in determining the air infiltration of buildings. Consequently, it is imperative to acknowledge that different climatic regions exhibit diverse air infiltration characteristics. However, there exists a dearth of analysis regarding the air infiltration features of highly airtight buildings across various climatic regions. Additionally, China is currently involved in the construction of a significant number of PHSBs [32]. Determination of the airtightness index is a crucial aspect to consider in achieving PHSBs.

This study took a PHSB with high airtightness (ACH₅₀, 0.5 h⁻¹) as the object, conducted numerical simulations of its AIR under the typical meteorological parameters of cities in the cold and severely cold regions of China, and analyzed the relationship between building air infiltration and its energy demand. This study provides theoretical guidance for designing buildings with high levels of airtightness.

2. Methods

2.1. Building Information

The building utilized in this study was a three-story PHSB boasting an internal volume of 3560.32 m³ and a usable floor area of 1408.37 m². It is situated in the cold region of China. The planar structure of this building is shown in Figure 1. The building, serving as a government demonstration project, exhibits commendable thermal performance. The primary design objective was to fulfill its heating requirements without the utilization of an active heating system, relying exclusively on efficient heat recovery mechanisms and internal sources of heat. The heat transfer coefficients of the building envelope (exterior walls, floor, and roof) were designed to be below 0.15 W/m²·K, while those of the outer doors and windows were to be below 0.8 W/m²·K. A well-balanced fresh air system with a heat recovery efficiency of 75% was devised to facilitate the introduction and exhaust of fresh and polluted air, respectively.

The size and number of the windows and doors of the building are shown in

Table 1. Dimensions and number of windows and doors [33].

Window/Door Code	Dimensions, m	Number
C2412	2.4 × 1.2	13
M1221	1.2 × 2.1	19
M0921	0.9 × 2.1	11
C0920	0.9 × 2.0	1
C0911	0.9 × 1.1	1
C1518	1.5 × 1.8	3
C2418	2.4 × 1.8	14
C0910	0.9 × 1.0	2
C0978	0.9 × 7.8	1
MQ0960	0.9 × 6.0	5

.

To enhance the building’s airtightness, special measures were implemented in both the design and construction processes [34]. These measures included incorporating highly airtight exterior doors, windows, and HVAC components; employing staggered splicing of two or three thermal insulation layers with reduced thicknesses; utilizing sealing rings/glue/tape for pipes passing through walls; applying sealing tape around window frames for external suspension outer windows; sealing reserved holes with sealant and sealing tape; and providing comprehensive training for high-quality construction personnel.

Although recent research has suggested alternative methods for determining envelope airtightness through suite-based testing [35,36], the findings indicate that these methods exhibit lower test accuracy compared to the traditional blower door test method. In our previous study [33], building airtightness was tested according to the standard EN 13829 [37]. The Minneapolis blower door test system was applied to depressurize and pressurize the building, and the differential pressure across the building envelope changed from 25 to 70 Pa at an interval of 5 Pa. Treatment of the openings in the building envelope was carried out in accordance with Method A described in EN 13829, i.e., measuring the airtightness of a building in use. During the test, the internal doors and windows were kept open to make it as close as possible to a single zone. The building airtightness test results are shown in

Table 2. Test results for the building airtightness [33].

Test Mode	Flow Coefficient, m3/(h·Pan)	Flow Exponent	Airflow at 50 Pa, m3/h	ACH50, 1/h
Depressurization	181.4 (±9.3%)	0.572 (±0.024)	1700 (±0.8%)	0.50
Pressurization	155.1 (±11.4%)	0.608 (±0.030)	1680 (±1.1%)	0.49

.

The airtightness level of the tested building demonstrated a significant improvement compared to that of NZEBs, as evidenced by a 17% increase in airtightness. These results indicate that the current building construction technology is capable of meeting the technical requirements for achieving an airtightness level of 0.5 h⁻¹.

2.2. Building Air Infiltration Simulation

The AIR prediction model UPFM [38] was utilized to predict the AIR of the tested building. This model incorporates the influence of impermeable components within the building and was developed based on the hypothesis of uniformly distributed air infiltration pathways throughout permeable areas. The impermeable portion encompasses the glass area of windows and doors, while the other sections of the building façade, such as the walls, roof, ground, and joints of window and door openings, are considered permeable. A hypothesis has been proposed regarding the distribution of adventitious openings in the building envelope: it assumes that these openings are uniformly and continuously distributed within the permeable building envelope, with an infinite number of them. The adventitious openings for windows and doors refer to their joint opening parts, which possess equal air permeability under identical conditions. The finite integral method was utilized to accurately predict air infiltration in both single- and multi-zone buildings with high airtightness.

The reliability and prediction accuracy of the model were initially tested by comparing the AIRs measured using the tracer gas attenuation method with those simulated by this model in 120 cases. The comparison results demonstrated a relative error of less than 10% [38].

The primary computational formulas are as follows:

$$q_{\mathrm{fa}\_i}=q_{w\_i}+q_{c\_i}$$

(1)

$$q_{w\_i}={\displaystyle \underset{0}{\overset{X}{\int }}{\displaystyle \underset{0}{\overset{Y}{\int }}\epsilon (\Delta P_i(y))\cdot C_{w\_i}\cdot {\left|\Delta P_i(y)\right|}^n}}dxdy-{\displaystyle \underset{x1}{\overset{x2}{\int }}{\displaystyle \underset{y1}{\overset{y2}{\int }}\epsilon (\Delta P_i(y))\cdot C_{w\_i}\cdot {\left|\Delta P_i(y)\right|}^n}}dxdy$$

(2)

$$\begin{array}{ll}{q}_{c\_i}& ={\displaystyle \sum _{j=1}^N{N}_{jv}\cdot {\displaystyle \underset{y_{j}1}{\overset{y_{j}2}{\int }}\epsilon (\Delta P_i(y_j))\cdot {\alpha }_1\cdot {\left|\Delta P_i(y_j)\right|}^b}dy}\\ & +{\displaystyle \sum _{j=1}^N{N}_{jh}\cdot \epsilon (\Delta P_i(y_j))\cdot {\alpha }_1\cdot {\left|\Delta P_i(y_j)\right|}^b\cdot (x_{j2}-x_{j1})}\end{array}$$

(3)

$${\displaystyle \sum _{i=1}^{n}f({\rho }_E,{\rho }_I)\cdot q_{\mathrm{fa}\_i}}=0$$

(4)

Both $\epsilon (x)$ and $f({\rho }_E,{\rho }_I)$ are binary functions, as shown below.

$$\epsilon (\Delta P)=\{\begin{array}{ll}1& \Delta P>0\\ -1& \Delta P<0\end{array}$$

(5)

$$f({\rho }_E,{\rho }_I)=\{\begin{array}{ll}{\rho }_E& \Delta P>0\\ {\rho }_I& \Delta P<0\end{array}$$

(6)

The AIR prediction model corresponding to the tested building was established by implementing the aforementioned formulas. The primary procedure unfolded as follows:

(1)

Building up a specific model of the building

When conducting the airtightness test, the building was treated as a single zone, and the internal doors and windows were intentionally left open. It is important to note that the resistance to air infiltration through cracks in the building envelope significantly surpasses that of air leakage through interior doors and windows. Consequently, this study disregarded the internal airflow resistance within the building and simplified it into a single-zone model.

The remaining assumptions were formulated for the purpose of constructing the simulation model, as illustrated below.

(a)

There was no furniture inside the building.

(b)

The building envelope was simplified to a plane of uniform thickness.

(c)

The ground floor of the building was impermeable.

(2)

Defining the air permeability coefficient of the building façade

During the airtightness test, the outer windows and doors were closed, resulting in no significant openings in the building envelope. Therefore, all air leakage paths were considered as small openings. The simulation model accounted for two components of building air infiltration: infiltration through uniformly distributed air leakage paths and that through window and door joints.

Due to engineering constraints, no field test was conducted to assess the airtightness of the building’s windows. Instead, their airtightness was determined based on the performance test report issued by the National Center for Quality Supervision and Test of Building Engineering in China. According to this report, the air permeability coefficient of window opening joints is 0.083 m²/(h·Pa^b); thus, this value was adopted as the air permeability coefficient for this specific type of joint.

The air permeability coefficient of the building envelope’s permeable section was determined using the following formulas:

$$C_w=\frac{q_w^{\prime }}{A_w\cdot {50}^n}=\frac{q_{50}^{\prime }-q_{c50}^{\prime }}{A_w\cdot {50}^n}$$

(7)

$$q_{50}^{\prime }=\frac{293.15}{101.325}\times \frac{P\cdot C\cdot {50}^n}{T}$$

(8)

$$q_{c50}^{\prime }=\frac{293.15}{101.325}\times \frac{P\cdot {\alpha }_1\cdot L_{\mathrm{wd}}\cdot {50}^b}{T}$$

(9)

Based on the airtightness test results for the building, the values of n and b were set to 0.59 (the average air flow exponent under two test modes). By substituting these parameters into Formulas (7)–(9), we obtained an air permeability coefficient of 0.079 m/(h·Paⁿ) for the permeable part of the building envelope, which is numerically smaller than the air permeability coefficient of the joints in the window openings.

(3)

Setting the properties of the building and the weather conditions

The driving force behind air infiltration through the building envelope is determined by wind and buoyancy pressures. The latter is influenced by temperature differentials between indoor and outdoor environments, while the former is affected by wind velocity and direction. Therefore, the environmental parameters required for simulation included indoor air temperature, indoor air relative humidity, outdoor air temperature, outdoor air relative humidity, outdoor atmospheric pressure, and outdoor wind speed and direction.

The indoor environmental parameters were set as follows: an air temperature of 20 °C and a relative humidity of 50%.

The outdoor environmental parameters were obtained from Appendix A of Design Code for Heating, Ventilation and Air Conditioning in Civil Buildings GB 50736-2012 [39], specifically the corresponding outdoor meteorological parameters of cities in China. Given that this study focused on buildings located in cold and severely cold regions, the design conditions for winter and summer were determined based on the meteorological parameters associated with 60 cities in cold regions and 49 cities in severely cold regions, respectively. The specific procedure for configuring the aforementioned values was as follows:

(a)

Winter design conditions

The calculated outdoor temperature for air conditioning in winter was taken as the outdoor air temperature. The calculated outdoor relative humidity for air conditioning in winter was considered as the relative humidity of outdoor air. The average outdoor wind speed of the dominant wind direction in winter was utilized as the outdoor wind speed. The dominant wind direction in winter was determined to be the wind direction. The alternative dominant wind direction was chosen when there were two main wind directions, instead of a calm wind. The atmospheric pressure was regarded as the outdoor air pressure. In cases where there were two dominant wind directions, excluding calm winds, another dominant wind direction was selected. The atmospheric pressure served as the outdoor air pressure.

(b)

Summer design conditions

The calculated outdoor temperature of dry air for air conditioning in summer was taken as the outdoor air temperature. The calculated outdoor relative humidity for ventilation was utilized as the relative humidity of outdoor air. The average outdoor wind speed of the dominant wind direction in summer was determined as the outdoor wind speed. The dominant wind direction in summer served as the wind direction.

Detailed meteorological parameters are shown in Supplementary Materials. The calculation formulas for the partial pressure of water vapor and air density [40] are as follows:

$$p_v=\phi \times {\mathrm{e}}^{\left\{59.484085-\left(\frac{6790.4985}{T+273.15}\right)-5.02802\cdot \left[\ln \left(T+273.15\right)\right]\right\}}$$

(10)

$$\rho =\frac{p_{bar}-0.37802\cdot p_v}{287.055\times (T+273.15)}$$

(11)

The building was oriented toward the north, and the wind coefficients for various building façades were calculated using Swami and Chandra’s wind pressure profile [41] specifically designed for low-rise buildings.

(4)

Solving the UPFM

The single-zone model corresponding to this building can be described as a nonlinear equation, and numerical integration methods along with an exhaust algorithm were employed to solve it.

2.3. Energy Demand Caused by Building Air Infiltration

The energy demand caused by building air infiltration was calculated based on the AIR simulation results and Formulas (12)–(15), wherein the latent heat and sensible heating load were counted under summer design conditions, and only a sensible heating load was counted under winter design conditions. The moisture content (d) in the air, the summer cooling load (Q_s), and the winter heating load (Q_w) resulting from the building air infiltration were computed using the following formulas:

$$d=622\frac{P_q}{p_{bar}-P_q}$$

(12)

$$h=1.0t+0.001d(2500+1.84t)$$

(13)

$$Q_s=1000\ast G(h_N-h_0)$$

(14)

$$Q_w=1000\ast cG(t_N-t_0)$$

(15)

3. Results and Discussion

3.1. Building AIR Simulation Results

The present study involved the simulation of building AIRs under typical meteorological parameters in 109 cities located in the cold and severely cold regions of China. The simulation results for the winter and summer design conditions are presented in Figure 2 and Figure 3, respectively.

The data presented in Figure 2 demonstrate that, under winter design conditions, the AIR ranged from 40 to 340 m³/h, with an average of 189 m³/h, for buildings located in cold-region cities. Furthermore, it was observed that buildings situated in severely cold-region cities exhibited a narrow range of AIR values, varying from 97 to 344 m³/h, with an average of 209 m³/h. Notably, these values surpass those recorded for buildings in cold-region cities.

The data presented in Figure 3 demonstrate that, under summer design conditions, the AIR for buildings in cold-region cities ranged from 125 to 423 m³/h, with an average of 185 m³/h. Similarly, for buildings located in severely cold-region cities, the AIR varied between 134 and 369 m³/h, with an average of 194 m³/h. It is noteworthy that in most cities, the AIR tended to be higher in severely cold regions.

3.2. Distribution Rule of Building AIR

The standard deviation (SD) and variation coefficient (VC) of the building AIRs in each climatic region are shown in

Table 3. SD and VC of the building AIRs in each climatic region.

Climatic Region	Winter Design Conditions		Summer Design Conditions
	SD, m3/h	VC	SD, m3/h	VC
Severely cold	47.70	0.25	53.08	0.25
Cold	59.95	0.32	56.23	0.29

. Table 3 shows that the AIRs of buildings in severely cold regions had the same degree of dispersion in winter and summer. However, in cold regions, the degree of dispersion of the AIRs of buildings in winter was higher than that in summer. On the contrary, all of the AIRs of buildings presented a relatively high VC, which means that the AIRs of buildings differed greatly from one city to another.

Figure 4 shows the frequency distribution of the simulation results of the building AIRs in different climatic regions. Figure 4 shows that the maximum frequency of the building AIRs in severely cold regions was located in the interval [200, 250] under winter design conditions, and that in the other climatic regions and under different design conditions, it was located in the interval [150, 200]. As for the variation trend, the frequency distribution of the AIRs in severely cold and cold regions under summer design conditions closely approximated a lognormal distribution, while under winter design conditions, it was closer to a normal distribution.

Regarding the range of the building AIRs under winter design conditions, there was little difference between severely cold and cold regions; however, under summer design conditions, the range of the building AIRs in cold regions was larger.

The statistical results revealed significant variations in the meteorological parameters across different climatic zones. Taking outdoor wind speed and air temperature, which are closely associated with building air infiltration, as an example,

Table 4. Air temperature and wind velocity in cold and severely cold regions.

Climatic Region	Winter Design Conditions						Summer Design Conditions
	Air Temperature, °C			Wind Velocity, m/s			Air Temperature, °C			Wind Velocity, m/s
	Max	Min	Avg	Max	Min	Avg	Max	Min	Avg	Max	Min	Avg
Severely cold	−8.3	−41.0	−24.6	6.4	1.6	3.6	36.4	20.8	30.9	6.6	1.6	3.4
Cold	−5.1	−21.5	−10.5	7.3	1.3	3.5	40.3	22.8	33.1	5.4	1.7	3.1

presents the statistical findings for their maximum, minimum, and average values. According to Table 4, the outdoor air temperature exhibited a notable decrease in severely cold regions compared to cold regions. Additionally, while there was a slight disparity between the minimum and average values for outdoor wind speed, a substantial difference existed among the maximum values.

The AIR of buildings is closely correlated with meteorological parameters. Given substantial variations in the meteorological parameters across different climatic zones, the distribution pattern of the building AIRs exhibited noticeable disparities among these zones. The diagram in Figure 5 demonstrates the distribution of AIRs for buildings across various climatic zones and design conditions. It is evident from Figure 5 that the spatial pattern of the AIRs varied significantly under different meteorological conditions. In severely cold regions under summer design conditions, the building AIRs generally increased, with a higher outdoor wind speed and outdoor air temperature. The maximum value occurred at an outdoor wind speed of 5.5 m/s and an outdoor air temperature of 22.8 °C, while the minimum value was observed for an outdoor wind speed of 3.5 m/s and an outdoor air temperature of 31.5 °C. Notably, when the wind speed ranged from 2 to 4.5 m/s and the outdoor air temperature ranged from 29 to 33 °C, there was a significant fluctuation in the building air permeability.

The overall building AIR in cold areas under summer design conditions initially increased and then decreased with increasing outdoor wind speed, while it decreased with rising outdoor air temperature. Its maximum value was observed at an outdoor wind speed of 3.6 m/s and an outdoor air temperature of 20.8 °C, whereas the minimum value occurred when the outdoor wind speed was 2.7 m/s and the outdoor air temperature was 30.6 °C. Under the operating conditions characterized by a wind speed range of 2 to 4.0 m/s and an outdoor air temperature range of 30 to 35 °C, the building AIR exhibited significant fluctuations.

Under winter design conditions in severely cold regions, the overall building AIR increased with higher outdoor wind speeds and initially decreased before increasing again with lower outdoor air temperatures. The maximum AIR value was observed at an outdoor wind speed of 6.4 m/s and an outdoor air temperature of −26.4 °C, while the minimum value occurred at an outdoor wind speed of 3.4 m/s and an outdoor air temperature of −19.1 °C. Throughout the entire range of meteorological parameters, the building AIR exhibited significant fluctuations.

The overall building air infiltration increased with an increasing outdoor wind speed and decreased with a decreasing outdoor air temperature under winter design conditions in cold areas. The maximum value was observed when the outdoor wind speed was 7.0 m/s and the outdoor air temperature was −13.0 °C, while the minimum value occurred at an outdoor wind speed of 1.9 m/s and an outdoor air temperature of −13.6 °C. The building air infiltration exhibited significant fluctuations across the entire range of meteorological parameters.

Furthermore, it is worth noting that, even within the same climatic zone, there were discernible variations in the AIRs of buildings. For instance, in cold areas under winter conditions, the maximum AIR of a building could reach up to 8.5 times higher than the minimum value. Similarly, in severely cold regions under winter conditions, this ratio reduced to 3.5 times, while in cold regions under summer conditions, it became 3.4 times, and in colder regions under summer conditions, it decreased further to 2.8 times.

The AIR of buildings is significantly influenced by the pressure differential across the building envelope, which results from a combination of wind pressure and stack effect pressure. The AIR typically increases with higher indoor/outdoor temperature differences and wind velocities, as demonstrated in Figure 5 through the AIR simulation results. However, apart from these environmental factors, numerous other parameters impact the AIR of a building, including wind direction, air leakage distribution, building structure, relative humidity levels, and atmospheric pressure.

The aforementioned factors render the law governing changes in building AIRs exceedingly intricate. For instance, due to a decrease in the wind pressure coefficient determined by the wind direction and building structure, the wind pressure on a façade may diminish as the wind speed increases, subsequently leading to a reduction in the AIR. In light of these combined influences, a building’s AIR fluctuates with increasing outdoor wind speed and air temperature.

The above results clearly indicate substantial variations in the distribution rules and values of building AIRs across different regions and design conditions.

3.3. Discussion

(1)

Air infiltration influence on building energy demand

Currently, highly airtight buildings, such as ultra-low energy buildings, passive houses, and NZEBs, are generally acknowledged to possess low AIRs, with minimal impact on the system design in terms of energy demand. Consequently, the influence of air infiltration is often disregarded during simulation and system design processes for these types of structures. However, there remains a lack of quantitative analysis regarding the energy implications associated with air infiltration in highly airtight buildings.

The heating and cooling loads of NZEBs located in the different climatic regions of China were simulated by Zhang [42], with their maximum values presented in

Table 5. Load comparison between air infiltration rates and buildings.

Climatic Region	Heating Load, kW		Ratio	Cooling Load, kW		Ratio	Building Type
	Building	Infiltration		Building	Infiltration
Severely cold	36.12	4.55	13%	24.10	2.44	10%	Residential building
Cold	20.15	2.92	15%	55.10	1.63	3%	Office building

. Although the building types simulated in the aforementioned study differ from that considered in this paper, the simulation results can serve as a valuable reference. In this study, the energy demand resulting from air infiltration under the design conditions was compared to the maximum load of the simulated buildings in each climatic region, as presented in Table 5.

The findings presented in Table 5 demonstrate that air infiltration contributes to over 10% of the total building heating load in both cold and severely cold regions. Additionally, it can be observed that air infiltration accounts for approximately 10% of the cooling load in severely cold regions.

The above results show that air infiltration has a great influence on the building load under the design conditions, even when the building airtightness is as low as 0.5 h⁻¹. Thus, the influence of air infiltration should not be ignored in the performance simulation and system design of highly airtight buildings, and the airtightness can be further enhanced on the existing basis for buildings in severely cold and cold regions.

(2)

Airtightness classification index

In the Technical Standard for NZEBs [3], the classification method for airtightness indices is based on climatic regions. Buildings of the same type in cold and severely cold regions are assigned identical airtightness indices. However, our findings indicate significant variations in building AIRs and energy demands across different cities within these climatic zones, as demonstrated in Section 2.1 of this study. This implies that applying the same airtightness limiting value in both cold and severely cold climatic regions would result in varying energy demands due to the differences in air infiltration among different cities within the same climatic region.

The energy demand resulting from building air infiltration in various climatic zones is illustrated in Figure 6. The data presented in Figure 6 demonstrate significant variations in energy demand due to air infiltration and its distribution range across different climatic zones, even when the building airtightness level remains constant. Under summer design conditions, the energy demand due to building air infiltration in cold areas was 1.55 times higher for maximum values, 1.62 times higher for minimum values, and 1.36 times higher for average values compared to severely cold areas. Similarly, under winter design conditions, the energy demand due to building air infiltration in severely cold areas was 1.56 times higher for maximum values, 2.85 times higher for minimum values, and 1.71 times higher for average values compared to cold areas. Furthermore, under winter design conditions, the distribution range of energy demand due to building air infiltration was significantly wider in severely cold areas than in cold areas; however, this situation was reversed under summer design conditions.

Based on the aforementioned analyses, it is suggested that the classification index of airtightness should be further refined and that different airtightness limits should be adopted for buildings even in the same climatic region. In order to solve this problem, it is necessary to further analyze the relationship between airtightness and energy demand due to building air infiltration for cities in the cold and severely cold climatic regions of China.

4. Conclusions

The air infiltration rate (AIR) and its corresponding energy demand for a passive house standard building with an airtightness level of 0.5 h⁻¹ were simulated and analyzed in this study, considering typical meteorological conditions for cities located in the cold and severely cold regions of China. The simulation results demonstrated that the building AIR ranged from 125 to 423 m³/h, with an average value of 189 m³/h under the summer design conditions; under the winter design conditions, the respective values were observed to be 40, 344, and 198 m³/h. The statistical results indicated significant variations in the building AIR across different climatic regions, both in terms of value and change patterns. Discussion of the findings revealed that, during winter, the energy demand resulting from air infiltration can exceed 10% of the building load, emphasizing the importance of considering its impact in performance simulation and system design for highly airtight buildings. Refinement of the classification index for airtightness is recommended, along with the adoption of varying airtightness limits for buildings in different regions of China.

This study offers recommendations for the design of highly airtight buildings in various climatic regions, with a specific building chosen as the subject of analysis. Additional extensive and in-depth research is imperative to attain a more compelling conclusion and establish a definitive classification index for highly airtight buildings. Additionally, it is crucial to consider the interplay between building watertightness and airtightness to derive more universally applicable conclusions regarding building energy demand.