**4.2.1 A model for decay development in pine sapwood**

There is always a vide variation within the growth condition of different fungus species, and we need overall evaluation on the growth activity and decay development of a "typical" example fungi like typical decay fungi (e.g. *Coniophora puteana* or *Gloeophyllum sepiarium*). VTT has done comprehensive research in mould and decay growth and their numerical modelling on timber (Viitanen 1996, Viitanen et al 2003) presented a model of decay development in pine and spruce sapwood.

Later a new model was developed from the work presented in references Viitanen and Ritschkoff (1991b), Viitanen (1996), and Viitanen (1997). In these references, the decay growth of brown rot in spruce and pine sapwood is studied experimentally in different constant relative humidity and temperature conditions. In the present model, only the data of pine sapwood is considered. Based on the experimental findings presented in references, a model for variable conditions is proposed (Toratti et al 2009)). This model is a time stepping scheme. The development of decay is modelled with two consecutive processes:

#### *a) Activation process:*

588 Mass Transfer - Advanced Aspects

The excessive water into the building structure and materials is the basic cause to different bio-deterioration problems like decay. For instance, in washrooms water often penetrates through inside surfaces or pipe leakage into the structures causing long lasting high humidity conditions. In old wooden buildings, the floor has often been built above a cold ventilated basement or crawl space, where high humidity conditions may exist. If water is penetrated in the crawl space, the ventilation may not keep the floor dry and mould growth is obvious. If ventilation caps are closed, severe decay problems have been found, e.g. dry

In connection of the decay, also microbial contamination on the surfaces in the crawl space is typically much higher than inside the building. The level of fungal spores in the crawl space is about ten times as high as indoors. In crawl spaces, spore concentrations in a range of 103-105 colony-forming units per gram (cfu/g) of material are common. The levels have usually been highest on wood-based boards and on timber (Hyvärinen et al. 2002). In cases of heavy fungal colonisation, airborne spore concentrations of up to 103-104 cfu/m3 have

The slab-on-ground structure without thermal insulation below the concrete slab has been used in old buildings. This type a floor is very sensitive for water damage and microbial growth. Especially in detached houses built between 1960 and 1980, wooden beams are often supported on concrete slabs on grade. Partial decay or insect damage is often found in the lower sill plate of exterior walls due to water penetration from the basement (Kääriäinen

Decay is the more severe result of high moisture exposure of wooden structures when the materials are wet for long periods. According to laboratory studies, the growth of decay fungi and decay development can start when the ambient humidity level in the microclimate remains for several weeks above RH 95 – 100 % and moisture content of pine sapwood above 25 – 30 % (Viitanen and Ritschkoff 1991b, Morris et al 2006). According to experience, decay will develop when moisture content of wood exceeds the fibre saturation point (RH above 99.9 % or wood moisture content 30 %, but also the variation of conditions

There is always a vide variation within the growth condition of different fungus species, and we need overall evaluation on the growth activity and decay development of a "typical" example fungi like typical decay fungi (e.g. *Coniophora puteana* or *Gloeophyllum sepiarium*). VTT has done comprehensive research in mould and decay growth and their numerical modelling on timber (Viitanen 1996, Viitanen et al 2003) presented a model of

Later a new model was developed from the work presented in references Viitanen and Ritschkoff (1991b), Viitanen (1996), and Viitanen (1997). In these references, the decay growth of brown rot in spruce and pine sapwood is studied experimentally in different constant relative humidity and temperature conditions. In the present model, only the data of pine sapwood is considered. Based on the experimental findings presented in references, a model for variable conditions is proposed (Toratti et al 2009)). This model is a time stepping scheme. The development of decay is modelled with two consecutive processes:

**4. Modeling of development of decay 4.1 Causes for decay damages in buildings** 

and temperature has an important effect.

**4.2 Modeling the decay development** 

**4.2.1 A model for decay development in pine sapwood** 

decay development in pine and spruce sapwood.

been detected.

et al. 1998).

rot damage (Paajanen and Viitanen 1989, Kääriäinen et al. 1998).

This is termed as α parameter, which is initially 0 and gradually grows depending on the air conditions to a limit value of 1. This process is able to recover in favourable conditions (dry air) at a given rate (although no experimental evidence of recovery is available).

#### *b) Mass loss process:*

This occurs when the activation process has fully developed (α=1) otherwise it does not occur. This process is naturally irrecoverable.

These processes only occur when the temperature is 0..30 °C and the relative humidity is 95% or above. Outside these condition bounds, the activation process may recover, but the mass loss process is simply stopped. The activation process is as given in Equation 2. The recovery time (i.e. α recovers from a value of 1 back to 0) is assumed to be 17520 hours (2 years). Recovery takes place when the conditions are outside the bounds of the decay growth.

The model can be used for evaluation the exposure condition for the eventual risk of decay to develop. For example, recorded temperatures and relative humidity are given for the Helsinki area. This climate is shown in the figure 1 for a one year period. According to the model, this climate seems to induce a low mass loss of 1.1 % in 4 years (Figures 4 and 5). During the first year, no decay development will occur in untreated pine sapwood. After 3 and 4 years exposure, decay is expected to occur only to a very limited extent in the surface of unprotected pine sapwood. Under normal use conditions, the cladding is protected by paints or other coatings. The direct influence of water on the wood surface is very small, and decay development will be significantly retarded or even negligible.

$$\begin{aligned} \text{Activation process } & \alpha = 0.1\\ \text{or} & \begin{aligned} \alpha(t) &= \prod\_{0}^{t} (\Lambda \alpha) \end{aligned} \text{ where} \\ \Lambda \alpha &= \frac{\Delta t}{t\_{crit}(\mathcal{R}H, T)} \text{ or (in favorable conditions of decay)} \end{aligned} \tag{10}$$

$$t\_{crit}(RH, T) = \left[\frac{2.3T + 0.035RH - 0.024T \times RH}{-42.0 + 0.14T + 0.45RH}\right] \times 30 \times 24 \text{ [hours]}$$

The mass loss process proceeds the activation process, when α has reached 1(Eq. 11).

Massloss process when 1 α ≥

$$\begin{aligned} ML(t') &= \int\_{t \text{ at } a = 1}^{t'} \frac{ML(RH, T)}{dt} dt = \sum\_{t \text{ at } a = 1}^{t'} \left( \frac{ML(RH, T)}{dt} \times \Delta t \right) \\\\ \frac{ML(RH, T)}{dt} &= -5.96 \times 10^{-2} + 1.96 \times 10^{-4} T + 6.25 \times 10^{-4} RH \left[ \% \ / \text{ hour} \right] \end{aligned} \tag{11}$$

For advanced decay to develop, a significantly longer period is needed, and after a 10 years period, severe decay in unprotected and uncovered pine sapwood can be expected in the Helsinki area. The design of details has a strongly marked effect on the durability and

Moisture and Bio-Deterioration Risk of Building Materials and Structures 591

Time [years] 1 2 3 4 5

Fig. 6. No activation of growth or decay development during the first and second years, an activation of decay process after 4 years exposure may be expected (Viitanen et al 2010b)

Fig. 7. a) Modelled mass loss (in %) of small pieces of pine wood that are protected from the

The risk of decay activity in different part of Europe can be evaluated on the map. If we evaluate the decay activity rate in Helsinki to be 1, then the decay risk in north-western part of Portugal and in West Ireland is 2 times and in Atlantic part of France and Belgium it will

rain or b) exposed to rain in 10 years in Europe (from [Viitanen et al. 2010b, 2011b)

Mass loss [%]

1.2

1

0.8

0.6

0.4

0.2

0

α

1.2

1

0.8

0.6

α

0.4

0.2

0

Mass loss [%]

service life of wood structure. If there is a detail collecting the water, the moisture conditions are suitable for long time for decay to develop. If the structure and details are well planned so that there is no water sink and the structure can be dried after occasionally wetting, the conditions for decay development will not be reached, and there are actually no limits for the service life of wood.

### **4.2.2 Evaluation of decay risk in different part of Europe using decay model**

The empirical wood decay model was run using the ERA-40 data for air temperature, humidity and precipitation at 6 hour intervals (Viitanen et al 2010b). ERA-40 is a massive data archive produced by the European Centre of Medium-Range Weather Forecasts (ECMWF). The reanalysis involves a comprehensive use of a wide range of observational systems including, of course, the basic synoptic surface weather measurements. The ERA-40 domain covers all of Europe and has a grid spacing of approximately 270 km. The nature of the data and the reanalysis methods of ERA-40 are described in detail in Uppala et al. [2005]. The evaluation of decay development in the model is based on the mass loss caused by the decay fungus. Within specified limitations, the mass loss is an applicable variable for evaluating the decay development in wood. The decay development model will give a general assumption of the effect of humidity, temperature and exposure time on the start and progress of the decay.

The resulting modelled mass loss in 1961-1970 at the calculation points of the ERA-40 grid were analyzed by a chart production software producing a maps of wood decay in Europe (Figure 7). First a map on decay risk protected from rain and then a map on decay risk of pine sapwood exposed to rain. A modification of the weather data was made so that the humidity of air was set to 100% during precipitation (at non-freezing temperatures) as this is thought to result in a full saturation in the wood surface.

Fig. 5. Measured climate data (Helsinki) used in the decay model for one year (Viitanen et al 2010b)

service life of wood structure. If there is a detail collecting the water, the moisture conditions are suitable for long time for decay to develop. If the structure and details are well planned so that there is no water sink and the structure can be dried after occasionally wetting, the conditions for decay development will not be reached, and there are actually no limits for

The empirical wood decay model was run using the ERA-40 data for air temperature, humidity and precipitation at 6 hour intervals (Viitanen et al 2010b). ERA-40 is a massive data archive produced by the European Centre of Medium-Range Weather Forecasts (ECMWF). The reanalysis involves a comprehensive use of a wide range of observational systems including, of course, the basic synoptic surface weather measurements. The ERA-40 domain covers all of Europe and has a grid spacing of approximately 270 km. The nature of the data and the reanalysis methods of ERA-40 are described in detail in Uppala et al. [2005]. The evaluation of decay development in the model is based on the mass loss caused by the decay fungus. Within specified limitations, the mass loss is an applicable variable for evaluating the decay development in wood. The decay development model will give a general assumption of the effect of humidity, temperature and exposure time on the start

The resulting modelled mass loss in 1961-1970 at the calculation points of the ERA-40 grid were analyzed by a chart production software producing a maps of wood decay in Europe (Figure 7). First a map on decay risk protected from rain and then a map on decay risk of pine sapwood exposed to rain. A modification of the weather data was made so that the humidity of air was set to 100% during precipitation (at non-freezing temperatures) as this is

0 2000 4000 6000 8000 10000

RH temp

**Time [h]**

Fig. 5. Measured climate data (Helsinki) used in the decay model for one year (Viitanen et al

**4.2.2 Evaluation of decay risk in different part of Europe using decay model** 

the service life of wood.

and progress of the decay.


2010b)


0

20

**Temp C or RH%**

40

60

80

100

thought to result in a full saturation in the wood surface.

Fig. 6. No activation of growth or decay development during the first and second years, an activation of decay process after 4 years exposure may be expected (Viitanen et al 2010b)

Fig. 7. a) Modelled mass loss (in %) of small pieces of pine wood that are protected from the rain or b) exposed to rain in 10 years in Europe (from [Viitanen et al. 2010b, 2011b)

The risk of decay activity in different part of Europe can be evaluated on the map. If we evaluate the decay activity rate in Helsinki to be 1, then the decay risk in north-western part of Portugal and in West Ireland is 2 times and in Atlantic part of France and Belgium it will

Moisture and Bio-Deterioration Risk of Building Materials and Structures 593

Hens, H.L.S.C. 1999. Fungal defacement in buildings: A performance related approach.

Hukka, A. and Viitanen, H. 1999. A mathematical model of mould growth on wooden

Hyvärinen, A., Meklin, T., Vepsäläinen, A. and Nevalainen, A. 2002. Fungi and

of Finland. 85 p. (VTT Research Notes 1923). 63 p. + app. 14 p. (in Finnish). Ojanen, T; Viitanen, H; Peuhkuri, R; Lähdesmäki, K; Vinha, J; Salminen, K. 2010. Mould

Paajanen, L. and Viitanen, H. 1989. Decay fungi in Finnish houses on the basis of inspected

Sedlbauer, K. 2001. Prediction of mould fungus formation on the surface of/and inside

Sedlbauer K. and Krus, M. 2003. A new model for mould prediction and its application in

Smith, S.L. and Hill, S.T. 1982. Influence of temperature and water activity on germination

Thelandersson, S.; Isaksson, T., Suttie, E., Früwald, E., Toratti, T., Grüell, G., Viitanen, H.

Uppala, S.M., Kållberg, P.W., Simmons, A.J., Andrae, U., da Costa Bechtold, V., Fiorino, M.,

Journal. of the Royal Meteoroogical Society, 131, 2961-3012.

applications. Proceedings IRG Annual Meeting 2011, IRG/WP 11-20465 Toratti, T; Viitanen, H; Peuhkuri, R; Makkonen, L; Ojanen, T; Jämsä, S..2009. Modelling of

diversity, International Biodeterioration and biodegradation 49:27-37. Kääriäinen, H., Rantamäki, J. and Tulla, K. Moisture Performance of Wooden Buildings.

material. Wood Science and Technology 33(6):475-485.

Research, Vol. 5, H 3, pp. 256-280

National Laboratory (ORNL) (2010), 10 p.

Preservation, IRG Doc. No: IRG/WP/1401. 4 p.

Physics, Doctoral thesis. Stuttgart. Germany.

International conference on Building Physics

University. Istanbul, Turkey (2009), 127-134

British Mycological Society, Vol. 79, H 3, pp. 558-560.

International Journal of Heating, Ventilation, Air-Conditioning and Refrigerating

actinobacterai in moisture-damaged building materials – concentrations and

Feedback Knowledge of Actual Buildings. 1998. Espoo: Technical Research Centre

growth modeling of building structures using sensitivity classes of materials. Thermal Performance of the Exterior Envelopes of Whole Buildings XI International Conference; (Buildingx XI), December 5-9, 2010, Clearwater Beach, Florida. Proceedings of Thermal Performance of the Exterior Envelopes of Whole Buildings XI International Conference (CD). DOE, BETEC, ASHRAE, Oak Ridge

samples from 1978 to 1988. The International Research Group on Wood

building components. University of Stuttgart, Fraunhofer Institute for building

practice. In Research in Building Physics. Ed. by Carmeliet, J. et al. Proc. of 2nd

and growth of Aspergillus restrictus and Aspergillus versicolor. Transactions of the

and Jermer, J. 2011. Quantitative design guideline for wood outdoors above ground

durability of wooden structures. 4th International Building Physics conference IBPC 2009, Istanbul, Turkey, 15-18 June 2009. Istanbul Technical

Gibson, J.K., Haseler, J., Hernandez, A., Kelly, G.A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R.P., Andersson, E., Arpe, K., Balmaseda, M.A., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B.J., Isaksen, L., Janssen, P.A.E.M., Jenne, R., McNally, A.P., Mahfouf, J.-F., Morcrette, J.- J., Rayner, N.A., Saunders, R.W., Simon, P., Sterl, A., Trenberth, K.E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J. 2005: The ERA-40 re-analysis. Quarterly

be between 2 and 2.5 times higher than that in Helsinki. In North Scandinavia it would be between 0.5 and 0.25, which will point out, the effect if climate on risk of decay development in outdoor structure varied vide within Europe. These coefficients can be used as one step to evaluate the effect of macroclimate conditions on service life of cladding and decking.

Another way to evaluate the macroclimate conditions is presented by Thelandersson et al (2011) using Meteonorm climate data. By calculating the daily dose and accumulating the dose for one year a measure of the risk of decay is obtained. This is made for several sites, and the result in terms of dosedays can be compared between the different sites. To be able to compare different sites, the dose was transferred to a relative dose by dividing it by the dose for the "base-station" Helsinki. Due to the variation of climate across Europe, relative doses between 0.6 (northern Scandinavia) and 2.1 (Atlantic coast in Southern Europe) were obtained.
