Analysis of indoor climate measurements in recently built Belgian dwellings

Transcription

1 Analysis of indoor climate measurements in recently built Belgian dwellings A. Janssens, A. Vandepitte Department of Architecture and Urban Planning Ghent University, Plateaustraat 22, Gent, Belgium Annex 41 Moist-Eng Working Meeting Lyon October, Introduction One of the major sources of problems usually met in Belgian dwellings -if not the main source- is moisture, especially due to surface and interstitial condensation in walls and roofs. The existing standards and reference documents related to moisture in dwellings are mainly based on researches dating from In the meanwhile, construction techniques and standardisation/regulation have changed a lot. Firstly, most dwellings were not yet properly insulated at that time. Secondly, dwellings were not yet equipped with any kind of ventilation systems. Thirdly, buildings usually were much less airtight; especially the air tightness of window and door joineries has been improved since the 80's. Consequently, dwellings became more energy efficient and more comfortable. The indoor climate is much better controlled than before when ventilation systems are used. On basis of these considerations, it seems necessary to evaluate if the reference documents related to moisture control in buildings are still relevant and, if not, to develop additional evaluation methods. This was the objective of the project "Moisture problems in roofs: impact of the present boundary conditions and construction techniques in Belgium", carried out by the Belgian Building Research Institute (BBRI), the Katholieke Universiteit Leuven (KUL), the Ghent University (UGent) and the Hogeschool voor Wetenschap & Kunst (High School for Science & Art W&K), and funded by the Belgian Government. In order to achieve this goal, it was necessary to collect data about the actual indoor climate in dwellings built since 1980; this was one of the project tasks. Measuring data were collected over a period of two and a half year ( ). The approach and set-up of the database of indoor climate measurements was presented in a previous paper (Heijmans, et al. 2004). This paper presents the analysis of the available data of vapour supply and indoor temperature. The results are related to differences in the dwelling types (private-social housing) and ventilation systems. The results are further compared to a similar analysis in a Finnish study (Kalamees 2006). The results discussed in this paper were part of a Master thesis (Vandepitte 2006). Monitoring campaign In order to collect a large number of data, 39 dwellings have been selected all over Belgium. Attention was paid in order to select various types of dwellings. The dwelling stock consisted of 18 social houses, 17 private single family houses of moderate size and 4 single family houses with a swimming pool. Other characteristics that were taken into account during the selection were the presence of a ventilation system according to the Belgian standard and the type of structure (traditional masonry versus wood-frame constructions). Table 1 gives an overview of the different types of dwellings. All of the private single family houses were detached houses, with approximately 65% built in the 1980 s, and 35% built after Of the social housing, the majority was semi-detached and a minor part (25%) consisted of apartments. An equal part of the social housing was built before and after Table 1 Ventilation system not in accordance to NBN D Ventilation system in accordance to NBN D Private single family 11 masonry houses 2 woodframe houses 3 masonry houses 1 woodframe house Social housing 14 masonry houses 4 masonry houses Private with swimming pool 4 masonry houses 1

2 The Belgian ventilation standard (1991) requires dwellings to have fresh air supply in living and sleeping rooms, and permanent air removal from polluted spaces like kitchens, bath rooms, washing rooms and toilets. The standard lists the design flow rates that may be achieved either by natural or mechanical ventilation. The application of this standard has only been made compulsive since January This is why the majority of houses from the measuring campaign do not have ventilation systems according to the standard. Still, in this group some houses may be equipped with ventilation devices in a limited number of rooms. In each dwelling, temperature and relative humidity were measured every 10 minutes, at six different locations: outside on site (sheltered from sun and rain), in the living room, in two sleeping rooms, in the kitchen and in the bathroom. The measurements are done with HOBO H8 Pro-dataloggers. The accuracy of these dataloggers is ± 0.2 C (at 21 C) and ± 3% RH (at 25 C). The monitoring period lasted from a minimum of 6 months (17 houses), over one year (16 houses) to a maximum of 2 years (6 houses). Therefore the database contains approximately days of measurements per room type. Several parameters were derived from the measured values of temperature and relative humidity: - for each location: the saturated vapour pressure p sat, vapour pressure p v and dew-point temperature, - for each indoor location: the indoor/outdoor vapour pressure difference, the critical temperature factor f Rsi,crit (which is a temperature factor with the dew point temperature taken as the indoor surface temperature) and the indoor surface temperature θ si corresponding to a temperature factor f Rsi equal to 0.7, - and average values for the building. The database contains therefore 46 parameters per dwelling, for each 10 minutes interval. This database would not be complete if there was no information available about the dwellings. For this reason, the occupant had to answer a questionnaire. This questionnaire included questions about the dwelling (type, location, insulation level ), its equipments (heating and ventilation systems ), the occupant's behaviour (number of occupants, time of occupancy ) and humidity (humidity related problems, source of humidity as aquariums ). The average occupation in the dwellings was 2.5 persons, with a minimum of 1 person (some apartments) and a maximum of 4 persons (a detached private house). These figures take account of the actual presence and absence of inhabitants during the week. Statistically there was no difference in occupation between private and social houses. Analysis of the moisture supply Methodology The analysis of the moisture supply was based on daily averaged values of the indoor to outdoor vapour pressure difference and the outdoor temperature. A similar analysis was also performed on weekly averaged data but this didn t show differences from daily averaged analysis. The analysis was done according to the assessment method described by Kalamees et al. (2006). Data from each room were sorted according to the outdoor temperature, using a 1 C step. The moisture supply data within each interval were then averaged. This resulted in a list of 39 data points per interval and per room (1 point for each dwelling). For the higher and lower extremes of outside temperature however, a smaller number of data points was available (Table 2). From these sorted values the maximum and minimum were calculated, together with the 95-, 50- (median) and 5- percentiles. Figure 1 shows the sorted values as averages over the 5 monitored rooms (1 line per dwelling). The method corresponds to the second method proposed by Kalamees. In the first method described by Kalamees, he takes the maximum weekly mean moisture supply value within each interval in stead of the average, as is done in this work. Table 2: Number of dwelling averaged data within each interval of outside temperature (-5;-4) (-4;-3) (-3;-2) (-2;-1) (-1;0) (0;1) (1;2) (2;3) (3;4) (4;5) (5;6) (6;7) (7;8) (8;9) (9;10) (10;11) (11;12) (12;13) (13;14) (14;15) (15;16) (16;17) (17;18) (18;19) (19;20) (20;21) (21;22) (22;23) (23;24) (24;25) (25;26) (26;27)

3 Vapour supply averaged over rooms daily mean vapour pressure difference (Pa) Figure 1: Vapour supply sorted per outside temperature interval, all dwellings: individual daily mean data, minimum, maximum, 95-, 50- (median) and 5-percentiles. Table 3: Variation of indoor climate classes with external temperature ICC Hens 1992 (355 weekly mean data, r² = 0.25) This study (data for -2 C<θ e <27 C) Limit p i -p e (Pa) Description Percentiles Regression r² 1 < *θ e 5% of dwellings 5% *θ e < *θ e 50% of dwelling s 50% *θ e < *θ e 95% of dwellings 95% *θ e > *θ e 5% of dwellings more humid Results of vapour supply values averaged over rooms The linear regression equations were defined for the 95-, 50- and 5-percentiles of the sorted vapour supply values. The values in the outside temperature interval (-5, -2) were not taken into account, because of the limited number of data compared to the other temperature intervals. The results are listed in Table 3 together with the limiting values between 4 indoor climate classes as defined by Hens (1992). He used the same percentiles to derive these limiting values. Figure 2 compares the data from this study to the limits between indoor climate classes. 800 Vapour supply averaged over rooms daily mean vapour pressure difference (Pa) Figure 2: Comparison between vapour supply percentiles and ICC according to Hens. 3

4 The comparison shows that the 5%-limit resulting from this study coincides with the border line between ICC 1 and 2, as proposed by Hens. The 50- and 95%-limits from this study however have shifted to lower values compared to the older analysis. This may be explained by the fact that some of the data in Hens analysis was from moisture damage cases, while the dataset applied in this study is more representative for normal conditions. The new lines are also less dependent of outside temperature (smaller slope) than before. The comparison to the indoor climate classes as proposed by the EN ISO (2001) is not made here anymore. Kalamees et al. (2006) already indicated the discrepancies between the EN-classes and his measuring data. The same disagreement may be seen for the results presented in this work. It is interesting to compare the trendlines derived above to the moisture supply curves proposed by Kalamees et al. (2006). His study was based on field measurements in 101 newly built detached houses in Finland. The indoor climate was continuously monitored during one year in living room, master bedroom and exterior of each house (sampling at one-hour intervals). Three vapour supply curves were derived: The design curve, derived from the maximum weekly mean vapour supply within each temperature interval, sorted according to outdoor temperature. The design curve was defined as the 90-percentile of these maximum values. The average curve, derived from the average vapour supply over the cold period (< 5 C) The minimum curve, derived from the minimum weekly mean vapour supply within each temperature interval, and defined as the 10-percentile of these minimum values. The vapour supply curves have constant values at outside temperature below 5 C and above 15 C with a linear part in between. Figure 3 makes the comparison. The design and the average curve derived by Kalamees are in agreement with the 95- and 50-percentiles resulting from this study. Also here a more constant vapour supply is measured at higher temperatures (deflection point at 15 C), and the vapour supply increases at colder temperatures. Only the bending point at 5 C is not visible in the Belgian data. On average the vapour supply measured during cold weather (< 5 C) in Belgium was 317 Pa (2.3 g/m³) with standard deviation 124 Pa (0.9 g/m³). During warm weather (> 15 C) the mean vapour supply was 71 Pa (0.5 g/m³) with standard deviation 92 Pa (0.7 g/m³). This is in agreement with the Finish study, where the average vapour supply during cold weather was 2.1 g/m³ (σ 0.9 g/m³) in naturally ventilated houses, and during warm weather 0.5 g/m³. 800 Vapour supply averaged over rooms daily mean vapour pressure difference (Pa) Figure 3: Comparison between vapour supply percentiles and moisture supply curves according to Kalamees. 4

5 Results of vapour supply values per room type Table 4 shows the regression equations for the 95- and 50-percentiles per room type. Also the mean vapour supply during cold weather (< 5 C) is given. The 5-percentile is not given because it was for all rooms in close agreement to the border line between ICC 1 and 2. There are four types of rooms: living rooms, kitchens, bath rooms and sleeping rooms (2 rooms per dwelling, consisting of both master bedrooms and children s rooms). The results show that the bath rooms are statistically the more humid rooms, followed by living rooms, kitchens and sleeping rooms. This is true for both the 5% critical level and the median values. This means that despite the fact that the bathroom is only intermittently used, the moisture load has a permanently high effect. This is probably related to the fact that bathrooms are poorly ventilated. Except for the bedrooms the 95-percentiles derived for the individual rooms are higher than the 95-percentile derived from the vapour supply values averaged over the rooms. Therefore it is better to use these local trend lines as an input to a moisture performance analysis. The results are compared to data given by Hens (2003). The 95-percentiles for night zone and bath room are in good agreement with our results. The values reported for living rooms are much higher than the results obtained in our study. Kalamees (2006) reported a mean moisture supply during cold weather of 257 Pa (1.9 g/m³) for bedrooms and 230 Pa (1.7 g/m³) for living rooms in Finnish houses. These are lower values than in the Belgian dwellings. This is probably related to the fact that the majority of Finnish houses in the measuring campaign had balanced ventilation systems, while the majority of Belgian houses rely on air leakage and window use for ventilation. Table 4: Trendlines for vapour supply per room This study Hens (2003) Δp ie (Pa) θ e < 5 C r² Δp ie (Pa) r² Living room 95% θ e 0,88 Day zone 95% θ e 0,53 (38 rooms) 50% θ e 313 Pa 0,93 (124 values) 50% θ e Kitchen 95% θ e 0,84 (31 rooms) 50% θ e 305 Pa 0,89 Sleeping room 95% θ e 0,83 Night zone 95% θ e 0,18 (72 rooms) 50% θ e 290 Pa 0,93 (177 values) 50% θ e Bath room 95% θ e 0,88 Bath room 95% θ e 0,64 (38 rooms) 50% θ e 368 Pa 0,93 (30 values) 50% θ e Private houses 95% θ e 0.89 (17 houses) 50% θ e 293 Pa 0.90 Social houses 95% θ e 0.88 (18 houses) 50% θ e 347 Pa 0.92 Difference between private houses and social houses The indoor climate in private houses and in social houses was separately analysed, see Table 4. The mean vapour supply during cold weather (< 5 C) in private houses was 293 Pa (σ 105 Pa). In social houses it was 347 Pa (σ 136 Pa). The social houses are clearly more humid than the private houses. As the occupation in both groups of houses was more or less the same, this difference is related to differences in geometry. On one hand the private houses are on average larger, resulting in a smaller moisture production per unit of floor area, or per unit of building volume. On the other hand the private houses were all detached, while the social houses were semi-detached or appartment buildings. Because of the larger compactness of the latter, the air tightness is better, resulting in smaller air infiltration rates and thus higher vapour pressures for the same moisture production. Typical n 50 -values for the Belgian housing stock are 9.5 h -1 for detached houses, 8.3 h -1 for semi-detached houses, 5.3 h -1 for terraced houses and 4.1 h -1 for flats (BBRI 1998). Analysis of the indoor temperature For the purpose of whole building HAM-modelling it is also important to understand how people use and heat their houses to have acceptable thermal comfort. In HAM-calculations it is not sufficient to characterise indoor conditions by the set-point temperature. It is also necessary to assess the actual temperatures resulting from building use. Certainly in mould growth analysis this is important. The same methodology was used as before to sort indoor temperatures according to outdoor temperature. Figure 4 shows the result of the analysis per room. 5

6 30 living room daily mean inside temperature ( C) bed rooms daily mean inside temperature ( C) bath room daily mean inside temperature ( C) Figure 4: Daily average indoor temperature dependence on daily average outdoor temperature: minimum, maximum, 95-, 50- (median) and 5-percentiles. The graphs show a strong dependency between inside and outside temperature for bed rooms and bath rooms. This indicates that these types of room are rarely heated in a large part of the investigated dwellings. The temperature in bed rooms is particularly low. At outside temperatures of 0 C, the daily mean bed room temperature is smaller than 16 C in 50% of the houses and even smaller than 12 C in 6

7 5% of the houses. The measurements also reveal uncomfortably hot conditions in part of the bed rooms during summer. The living rooms on the other hand are more continuously heated: at daily mean outside temperatures below 15 C the inside temperature becomes less dependent of outside temperature. At outside temperatures of 0 C, the daily mean inside temperature in the dwellings varies between 17.5 C (5%) and 22.5 C (95%). This band width corresponds to the comfort zone band width for PPD = 10%. Conclusions In the frame of the "Moisture problems in roofs" project, the indoor climate has been extensively monitored in 39 Belgian dwellings. This monitoring includes temperature and humidity measurements outside and in five rooms of each dwelling. The monitoring period varies from 6 to 24 months. These measurements give a better overview of the indoor climate of Belgian dwellings. In particular, they allow to evaluate the internal humidity classes typically met in dwellings and to select the most appropriate method to assess the moisture risk in a dwelling. These data could also be used in other researches, both at Belgian or international levels, as the measurement database is available to the scientific community. Acknowledgement The authors want to gratefully thank the Federal Public Service Economy, SMEs, Self-employed and Energy of the Belgian Government, which has funded the project "Moisture problems in roofs: impact of the present boundary conditions and construction techniques in Belgium". References Heijmans, et al. Setting up a database of indoor climate measurements in recently built Belgian dwellings. AIVC Conference 2004, Praha Vandepitte, A. Analyse van binnenklimaatmetingen in woningen. (Analysis of indoor climate measurements in dwellings, in Dutch), Master thesis , Department of Architecture and Urban Planning, Ghent University. NBN D Woningventilatie. Belgisch Normalisatie Instituut BIN. Kalamees T., Vinha J., Kurnitski J Indoor humidity loads and moisture production in lightweight timber-frame detached houses. Journal of Building Physics. Vol. 29/3, Hens, H Indoor climate classes. IEA-Annex 24 Internal Report T2-B-92/02. Hens, H Toegepaste bouwfysica 1: randvoorwaarden, prestaties en materiaaleigenschappen. Acco, Leuven. Janssens A. and H. Hens Development of indoor climate classes to assess humidity in dwellings. Proceedings of the 24 th AIVC-Conference, Ventilation, humidity control and energy, Washington DC EN ISO Hygrothermal performance of building components and building elements internal surface temperature to avoid critical surface humidity and interstitial condensation. CEN. BBRI Isolatie, ventilatie en verwarming in nieuwbouwwoningen. Resultaten van het SENVIVV onderzoek. Belgian Building Research Institute, Brussels. 7