Airtightness of Estonian dwellings – median and base-values for heat loss estimation.

The field measurements of airtightness in Estonian detached houses and apartment buildings, conducted between 2003 – 2022, were combined into a large dataset for statistical analysis. The buildings (539 in total) constructed between 1810 and 2022 were classified based on dwelling type, building structure, number of storeys, year of construction, energy classification and compactness factors. The data was statistically analysed to determine the mean and median air leakage rates at 50 Pa and tested (Kruskal-Wallis test with post-hoc Conover test) for significant differences within the grouping factors. Buildings constructed after the enforcement of the compulsory Energy Performance certification have on average across all building structure types significantly lower mean air leakage rate (1.6 m³/(h·m²)) than older buildings (6.9 m³/(h·m²)), although log-wood and brick construction types feature slightly higher average air leakage rate. Previous experience with air leakage measurements help to achieve better airtightness on building site. A systematic and recurring measurement practice within a single construction company leads to significantly lower air leakage also for new concrete buildings. Detailed assessment of older buildings showed that all timber-based construction types had significantly higher air leakage rate along with higher variability compared to precast large concrete panel stone and small block wall and brick buildings. All apartment buildings built before 2010 had significantly lower air leakage rate compared to detached houses while there was no difference in new buildings. Along with the mean and median value a base value of air leakage rate q_E50,base was calculated for all construction types and age groups including 50% of measured buildings around the mean within each group with 84 % confidence interval. The calculated mean, median and base values of air leakage rate provide a way for more accurate heat loss estimation at the district-level or building-level modelling of energy saving potential of different retrofitting strategies based on building age, construction type and other building information data.