*3.3. Building Energy Performance Assessment Methods*

The main requirements of building energy performance related to EPBD (European Energy Performance of Buildings Directive) [1,2] are described in Building Technical Regulation STR 2.01.02: 2016 [58]. Using the building energy consumption evaluation methodology with the application of outside temperatures derived from many years of observations, it is accepted that the duration of the heating season exceeds 220 days, the average outside temperature of the heating season is 0.6 ◦C, and the inside temperature of the premises is 20 ◦C. The index of total heat energy loss calculated per 1 m<sup>2</sup> heated area of building throughout the year is one of the assessment criteria used in the said methodology. In general, it can be expressed by the following equation:

$$\mathbf{Q}\_{sum} = \frac{\mathbf{Q}\_{env} + \mathbf{Q}\_{vent} + \mathbf{Q}\_{do} + \mathbf{Q}\_{inf} - \mathbf{Q}\_{\varepsilon} - \mathbf{Q}\_{i}}{\eta\_{h.s.}} + \mathbf{Q}\_{E} + \mathbf{Q}\_{h.w.} \tag{1}$$

where: Q*env* is the calculated heat loss through building envelope for 1 m2 of heated floor area throughout the year, kWh/m2·year;

<sup>Q</sup>*vent* is the calculated energy consumption for ventilation, kWh/m2·year;

<sup>Q</sup>*do* is the calculated heat loss due to entrance door opening, kWh/m2·year;

Q*inf* is the calculated heat loss due to excessive air infiltration through windows and external doors, kWh/m2·year;

<sup>Q</sup>*<sup>e</sup>* is the heat gain in the building due to solar radiation, kWh/m2·year;

<sup>Q</sup>*<sup>i</sup>* is the heat gain from internal heat sources, kWh/m2·year;

<sup>Q</sup>*<sup>E</sup>* is the annual electricity consumption, kWh/m2·year;

Q*h*.*w*. is the annual energy consumption from domestic hot water, kWh/m2 year;

η*h*.*s*. is the efficiency coefficient of building heating system, in part of a unit.

The aim was to evaluate the differences between the heat energy loss of the flats located in different parts of the same type buildings. Some of the formula components may be underestimated considering all the flats are operated in equal conditions. These components include heat loss because of external door opening, natural ventilation, electric power, and domestic hot water consumption. Since all the flats are designed with almost identical transparent enclosures, the heat increase resulting from direct solar radiation through the windows can be assessed as being the same.

Minor exceptions can be found in some rear facades of the end units. Because of different architectural solutions, some of these facades have one additional window with an area of around 2 m2. Therefore, during the thorough investigation of the buildings, some circumstances were found in this particular context of the built environment: most of the facades in question were not fully exposed to solar radiation for a longer time because of their shadowing by existing trees and buildings, most of the walls had East and West orientation, a large part of these windows were equipped with roller shutters, and a number of the flats did not have the additional window at all. Because of these factors substantially diminishing the solar heat energy gains, all end units were considered as solar radiation invariant in this research.

Excluding all these components mentioned above, the difference of the heat energy loss between the flats of different locations may be represented as:

$$\mathbf{Q}\_{sum(difference)} = \mathbf{Q}\_{env\ (difference)} + \mathbf{Q}\_{inf\ (difference)} \tag{2}$$

where:

$$\mathbf{Q}\_{env} = \frac{0.001 \cdot \mathbf{t}\_m \cdot \mathbf{24}}{\mathbf{A}\_p} \cdot (\boldsymbol{\Theta}\_{iH} - \boldsymbol{\Theta}\_{c,m}) \cdot \sum\_{\mathbf{x}=1}^{n} (\mathbf{A}\_{env} \cdot \mathbf{U}\_{env}) \tag{3}$$

and

$$\mathbf{Q}\_{\rm inf} = 0.001 \cdot \mathbf{t}\_m \cdot 24 \cdot \rho\_{air} \cdot \mathbf{c}\_{air} \cdot \mathbf{v}\_{\rm inf,m} \cdot \left(\boldsymbol{\Theta}\_{\rm iH} - \boldsymbol{\Theta}\_{\rm t,m}\right) \tag{4}$$

where:

t*m* is the number of days for the appropriate month of the year; A*<sup>p</sup>* is the heated area of the building, m2; θ*iH* is the internal temperature of the building during the heating season ◦C; θ*e,m* is the average air temperature of the appropriate month, ◦C; A*env* is the area of the building envelope, m2; <sup>U</sup>*env* is the U-value of the building envelope, W/m2·K; ρ*air* is the air density, kg/m3

> vinf,m= 0.25·n50·(0.75· ρ*air* <sup>2</sup>·<sup>50</sup> ·(0.9·v*wind*,*m*) 2 ) n · V*p*.*n*<sup>50</sup> A*p* (5)

where:

n50 is the air exchange value of the building, h−1; v*wind*,*<sup>m</sup>* is the average wind speed of the month, m/s; V*p*.*n*<sup>50</sup> is the volume of heated premises of the building, m3.

#### **4. Results**

#### *4.1. Analysis of Building Airtightness*

The airtightness of buildings is very much dependent on the quality of construction works and even the small mistakes can lead to significant differences in airtightness;

therefore, the evaluation of airtightness results was based on the comparison of statistical averages of the flats of the same type (Figure 3).

**Figure 3.** Airtightness measurement distribution for the flats of different floor areas.

The recorded results show that the values of airtightness of the flats with the same floor area can vary in a large range reaching the difference up to two times. The analysis of airtightness values of the flats of different floor areas revealed that the statistic average of results gradually decreases with the increase of the floor area of the flat, but the overall measurement scatter remains almost constant. The comparison of the groups of flats of 90 m2 and 200 m<sup>2</sup> floor area showed that the average value of airtightness for the flats with larger floor area is 25% smaller. The obtained results can be interpreted as the achievement of better average airtightness measurement result for the flats with a larger floor area and the same time a larger volume. This fact of the better results for larger flats could be explained as a minor defect that has a smaller effect on the general result of the airtightness of the building.

After the study of two material alternatives, such as hollow clay masonry units (also known as ceramic small blocks) (1) and sand–lime blocks (2) used for the construction of external walls, it can be stated that regardless of the floor area, airtightness values for hollow clay masonry walls were higher than the respective values for the more favourable sand–lime block walls. The processed data of the airtightness measurements of the equalarea flats located in different places of the buildings are presented in Table 2. The differences in statistical averages of the measurements reach 7–11%. When interpreting the results, the following reasons can be pointed out regarding this aspect. First, in the case of the structure of hollow clay masonry units, where the bricklaying technology requires only to fill the horizontal seams of the brickwork with the mortar, the air can circulate easier through many empty vertical seams in the wall. Second, in the case of hollow clay units, the air can circulate more freely in the structure because of the internal hollows of the elements. In addition, uncontrollable air can enter the room through the openings made for the installation of electric outlets through the other hollows that were not carefully tightened, and thus increase the air leakage in the building.

Additional information about this issue will also be given in the next chapter which concerns thermographic photo research.

A graphical illustration of the contrast of airtightness distribution data for end and inside units in the buildings with the walls of sand–lime blocks is shown below (Figure 4).

The general analysis and comparison of the data shows that the average values of airtightness in end units are 20% higher than the values in inside units of the same type.

Based on the research results, mathematical dependencies were derived to be used for the forecasting of airtightness values for the flats with various floor areas (Figure 5).

R-squared (R2) value in both flat location cases is close to 1, which indicates a high predictive quality of these models.


**Table 2.** Measurement values of the airtightness of the flats.

**Figure 4.** Airtightness of buildings with walls of sand–lime blocks, end units (**a**), and inside units (**b**).

**Figure 5.** Dependency diagrams of airtightness and floor area for the end (orange) and inside (blue) units in the sand–lime buildings of energy efficiency class A.

The comparison of statistical airtightness measurement data with the main metrics n50 (h−1), mainly of small and medium-size low-rise residential buildings along with the national regulation values from various countries, is provided below (Table 3). The juxtaposition of earlier and the newest data show an improvement in airtightness quality in recent years in Lithuania. Another noticeable trend is better airtightness values of Northern European countries and Canada, despite various construction periods of buildings. Airtightness in countries such as the UK and Ireland seems to be worse because of a very broad period of the building samples. Interesting outstanding results were obtained from a study of relatively new Passive House buildings in Germany.




Notes: "n50" air change rate at 50 Pa pressure difference, "*x*" mean, "*σ*" standard deviation or "*σSn*" deviation estimated from Snedecor's rule. If any value is not indicated it was not available.

> Relatively large standard deviation values of airtightness measurements can be noticed in some lines of the summary above. One of the implicit main reasons for this could be the broad construction period of buildings examined in the studies. The other significant factor is the relatively high airtightness limit value indicated in the regulation or the absence of any definite requirements in some countries. These factors lead to different levels of construction work by different companies and greater inequality of airtightness values.
