the effect of combining a relative-humidity-sensitive ventilation system with the moisture-buffering...

8/14/2019 The Effect of Combining a Relative-humidity-sensitive Ventilation System With the Moisture-buffering Capacity of

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The effect of combining a relative-humidity-sensitive ventilation system with

the moisture-buffering capacity of materials on indoor climate and energy

efficiency of buildings

Monika Woloszyn a,b,c,, Targo Kalamees d, Marc Olivier Abadie e,f, Marijke Steeman g,Angela Sasic Kalagasidis h

a Universite de Lyon, Lyon F-69003, Franceb Universite Lyon1, Villeurbanne F-69622, Francec INSA-Lyon, CETHIL UMR CNRS 5008, bat. Sadi Carnot, F-69621 Villeurbanne cedex, Franced

Chair of Building Physics and Architecture, Tallinn University of Technology, Ehiteja tee 5 19086, Estoniae Pontifical Catholic University of Parana PUCPR/CCET-Thermal Systems Laboratory, Rua Imaculada Conceic- ao, 1155 Curitiba, PR 80215-901, BrazilfLEPTIAB-University of La Rochelle, Avenue M. Crepeau, 17000 La Rochelle, Franceg Department of Architecture and Urban Planning, UGENT-Ghent University, J. Plateaustraat 22, 9000 Ghent, Belgiumh Department of Building Technology, Chalmers University of Technology, Sven Hultins gata 8, 412 96 Gothenburg, Sweden

a r t i c l e i n f o

Article history:

Received 23 November 2007

Received in revised form

20 April 2008

Accepted 22 April 2008

Keywords:

Whole building HAM simulationRelative-humidity-sensitive (RHS)

ventilation system

Moisture-buffering

Energy

Indoor climate

a b s t r a c t

Indoor moisture management, which means keeping the indoor relative humidity (RH) at correct levels,

is very important for whole building performance in terms of indoor air quality (IAQ), energy

performance and durability of the building. In this study, the effect of combining a relative-humidity-

sensitive (RHS) ventilation system with indoor moisture buffering materials was investigated. Four

comprehensive heatairmoisture (HAM) simulation tools were used to analyse the performance of

different moisture management strategies in terms of IAQ and of energy efficiency. Despite some

differences in results, a good agreement was found and similar trends were detected from the results,

using the four different simulation tools. The results from simulations demonstrate that RHS ventilation

reduces the spread between the minimum and maximum values of the RH in the indoor air and

generates energy savings. Energy savings are achieved while keeping the RH at target level, not allowing

for possible risk of condensations. The disadvantage of this type of demand controlled-ventilation is

that other pollutants (such as CO2) may exceed target values. This study also confirmed that the use of

moisture-buffering materials is a very efficient way to reduce the amplitude of daily moisture

variations. It was possible, by the combined effect of ventilation and wood as buffering material, to keep

the indoor RH at a very stable level.

& 2008 Elsevier Ltd. All rights reserved.

1. Introduction

Indoor moisture management, which means keeping theindoor relative humidity (RH) at correct levels, is very important

for whole building performance in terms of indoor air quality

(IAQ), energy performance and durability of the building envel-

ope. Indeed, indoor air humidity strongly affects indoor climate.

The main risk factors related to low RH may be associated with

the dryness of the skin, mucous membranes, sensory irritation of

the eyes and upper airways [13] as well as control of static

electricity [4,5]. The risk factors of having high RH are connected

with serious moisture problems for the building envelope and for

the indoor climate [610], due to the growth of micro-organisms

[11,12] and house dust mites [1315].Indoor air moisture is influenced by several factors, such as

moisture sources (human presence and activity, equipment), air

change rate and airflow in rooms, the release or uptake of

moisture by hygroscopic surfaces of envelope and furniture,

moisture flow through building envelope, possible condensation

as well as moisture content of the outdoor air. Adequate

ventilation is used in general in order to guarantee good IAQ

and to keep the indoor RH at a target level. The effect of

ventilation and resulting indoor humidity has a considerable

impact on the energy performance of the building, especially in

modern, very well insulated dwellings, where the part of the heat

loss due to air renewal can account for as much as half of the total

heat loss [16].

ARTICLE IN PRESS

Contents lists available at ScienceDirect

journal homepage: www.elsevier.com/locate/buildenv

Building and Environment

0360-1323/$- see front matter & 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.buildenv.2008.04.017

Corresponding author at: INSA-Lyon, CETHIL, bat. Sadi Carnot, F-69621

Villeurbanne cedex, France. Tel.: +33472 436 269; fax: +33 472438 811.

E-mail address: [email protected] (M. Woloszyn).

Building and Environment 44 (20 09) 515 524
http://www.sciencedirect.com/science/journal/baehttp://www.elsevier.com/locate/buildenvhttp://dx.doi.org/10.1016/j.buildenv.2008.04.017mailto:[email protected]:[email protected]://dx.doi.org/10.1016/j.buildenv.2008.04.017http://www.elsevier.com/locate/buildenvhttp://www.sciencedirect.com/science/journal/bae


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It is anticipated that the reduction of the amount of fresh cold

air introduced into the building contributes to bringing down

energy consumption. Evidently, the reduction of ventilation rates

must be carefully designed to prevent deterioration of IAQ,

including RH and pollutant levels. Previously conducted studies

showed that humidity can be successfully used as a control

parameter for ventilation, enabling energy savings without

compromising IAQ throughout the whole year (both in cold andmild months). This is directly related to the reduction of mean

ventilation rate, when the building is not used [17,18]. However,

for dwellings with very high moisture load, the RHS ventilation

may be used to improve IAQ, but lead to higher energy use [19].

Moreover, relevant use of the moisture-buffering capacity of

building materials contributes to stabilise the indoor climate in

terms of variations of RH. For example, Ref. [20] showed that in

the case of peak vapour production in the kitchen, about half of

the produced vapour was absorbed by the materials. This

moisture-buffering effect of materials was preventing surface

condensation.

All these interactions of indoor air humidity are complex, and

realistic predictions of different factors require the use of

advanced simulation tools. Simulation tools should be able totake the whole building into account and calculate room air

humidity including exchange of moisture between indoor air and

materials in contact with the indoor air. Several studies [2024]

have shown that the moisture storage capacity of finishing

materials has a significant effect on indoor RH and models that

do not include the sorption process do not adequately model

indoor RH. Mendes et al. [25] showed that whole-building energy

simulation models that ignore moisture transfer in the building

envelope may overestimate conduction peak loads up to 210% and

underestimate the yearly integrated heat flux up to 59% that can

lead to oversize heating, ventilation and air conditioning equip-

ment (especially in dry climates) and underestimate energy

consumption (primarily in humid climates).

In this work, the possibilities of combining an RHS ventilation

system with moisture-buffering capacity of materials were

investigated with whole building HAM simulation tools. At the

same time, four different simulation tools were tested to analyse

the performance of different indoor moisture management

strategies in terms of IAQ and of energy efficiency. Different

simulation tools were used for two reasons: (1) to avoid any

specific tool-related inaccuracy and (2) to compare capabilities

and possible differences of different tools for assessing indoor

moisture management issues.

2. Methodology

2.1. Studied configuration

The simulation case is based on a real one-storey test building

(see Fig. 1) with two rooms (volume 49.4 m3, area 19.3 m2), which

are located at the outdoor testing site of the Fraunhofer-Institute

of building physics in Holzkirchen, Germany (altitude: 680 m NN;

latitude: 47.881, north; longitude: 11.731, east).

The walls of the rooms were built with 24cm brick and

externally insulated with 7 cm polystyrene. The internal surface in

the reference room was standard gypsum plaster with a latex

paint. The walls and the ceiling of the test room were first fully

coated with aluminium foil and then (in some cases) covered with

manufactured gypsum board (see Table 1). The roof was an 18 cm

concrete slab, insulated with 20 cm polystyrene. A 25 cm concretefloor was insulated with 20 cm polystyrene and covered with PVC

linoleum. Such material properties as density, porosity, specific

heat capacity, thermal conductivity, moisture permeability, and

moisture retention curve were measured in laboratory conditions

and are described more in detail in Refs. [26,27].

The indoor air temperature was held at 201C, using a

temperature controlling electric heater in the centre of the room.

A ventilation system provided constant air change, determined by

tracer gas measurements (n 0.63h1 for the reference room and

n 0.66h1 for the test room). To achieve a realistic assessment

of the course of RH with regard to the moisture-buffering effect,

2.4 kg of water was introduced by an ultrasonic evaporator into

each room per day, which corresponds to the equivalent amount

for a household of three persons [28].

To differentiate short- and long-term moisture-buffering of

surrounding surfaces, two moisture production cycles were

chosen for each day: short but high moisture production in the

morning from 6 to 8 a.m. (0.4 kg/h) and larger but moderate

moisture production in the afternoon from 4 to 10p.m. (0.2 kg/h).

ARTICLE IN PRESS

Fig. 1. View and ground plan of test rooms: left-reference room with gypsum plaster and paint, and right-test room where different finishing materials were tested.

Table 1

Original finishing materials from experimental rooms

Room Step 1 (17/0102/02) Step 2 (14/0219/03) Step 3 (28/0321/04)

Reference (ach 0.63 h1) Gypsum plaster+paint Gypsum plaster+paint Gypsum plaster+paint

Test (ach 0.66 h1) Aluminium foil Gypsum board on walls Gypsum board on walls+ceiling

M. Woloszyn et al. / Building and Environment 44 (2009) 515524516


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These peaks simulate taking showers, washing, cooking and the

presence of human beings. The temperature of the wall surfaces,

temperature layering in the middle of the rooms, and RH in the

rooms, as well as energy consumption of the heating system, were

measured. The temperature and humidity in the centre of the

room were considered for comparison. For outdoor boundary

conditions, recorded weather data from Holzkirchen (January to

April 2005) were used. In constant indoor temperature, indoor RHdepends on moisture production, air change rate, outdoor

humidity by volume and on moisture flow exchanged between

indoor air and building envelope. Two first parameters are the

same in all steps. Outdoor humidity by volume was approximately

the same in steps 1 and 2. In step 3, the outdoor humidity by

volume was higher (see Fig. 2). Steps 1 and 2 presented cold and

dry external conditions, and step 3 mild and humid ones.

The influence of different ventilation system strategies and

moisture-buffering capacity of the internal surface of finishing

materials of building envelope on indoor RH were investigated. In

some configurations, a constant airflow ventilation system was

replaced by a RHS exhaust, where the ventilation airflow was

controlled by the room RH level. Such a system adapts the airflow

to changes in the indoor relative RH, as shown in Fig. 3 withRH1 25%, Q1 10m3/h, RH2 60%, Q2 40 m3/h. In some

configurations, the moisture-buffering properties of the internal

surface of finishing materials of the building envelope were

changed.

To study the influence of the ventilation system and properties

of finishing materials, simulations were performed with five

simulation runs (see Table 3):

Run A: Experimental data, with constant ventilation (validationof the simulation models),

Run B: Using original finishing materials (Table 1) and the

original RHS ventilation system (Fig. 3), Run C: Using original finishing materials (Table 1) a n d a

modified RHS ventilation system with modified maximum

(Q2) and minimum (Q1) airflow values (ventilation was

modified independently by the participants of the study),

Run D: Using the original RHS ventilation system (Fig. 3), butchanging the moisture-buffering properties of materials

(materials were chosen independently by the participants of

the study), and

Run E: Combining boththe ventilation and the materialsin order to reduce the energy consumption and to improve

indoor RH.

2.2. Simulation tools

Four different commercially available simulation tools were

used by five different institutions (see Table 2). All are whole-

building simulation tools: multi-zone tools for building simula-

tion of energy consumption, IAQ and thermal comfort in dynamic

conditions, under the influence of the outdoor climate and

variable loads. The different envelope parts (roof, walls and floor)

may separate the zones from each other and from the outdoors.

The geometry, material layers and their properties define the

envelope parts. The envelope may include a number of openings,

leaks, doors, and windows. Different heating, cooling, ventilation,

and lighting systems can be attached to rooms. Heat balances may

involve the heating/cooling devices, air handling units, elements

of the envelope, direct sun gains through windows, leaks and

thermal bridges, the internal thermal mass, occupants, lights,equipment.

All four simulation tools include the main elements of

moisture balance, discussed for example in Refs. [20,26,29]:

vapour sources (occupants, equipment, etc.), airborne transport

(air handling units, leaks, inter-zone flow) and sorption by

materials in contact with the indoor air. The models of moisture

flow between the indoor air and materials depend on the

modelling of heat and moisture transfers in the elements of

building envelope. Two tools can represent coupled heat and mass

transfers in the envelope (IDA-ICE and HAM-Tools) and two use

simplified models to represent the buffering effect of hygroscopic

materials (TRNSYS and Clim2000). In the following, the main

elements of moisture-buffering modelling are described, and

reference is made to the literature for further details of the

physical models used in the simulation tools.

2.2.1. Moisture transfer through the envelope parts

2.2.1.1. Coupled heat and mass flow models. Detailed, one-dimen-

sional coupled heat and water vapour transfer models are im-

plemented in IDA-ICE and HAM-Tools. Both are based on similar

equations, and suppose that moisture transfer is governed by one

moisture transfer potential, the humidity by volume, v (kg/m3).

The governing equations for the moisture (1) and energy (2)

transfer are then:

qv

qt

q

qxdv

qv

qx

, (1)

rcqTqt

qqx

l qTqx

hvap qv

qt, (2)

ARTICLE IN PRESS

Fig. 2. Outdoor conditions for all three steps.

Relative

Humidity (%)

Q2

Q1

RH1

Air flow(m3/h)

RH2

Fig. 3. Original RHS ventilation system test room (no moisture-bufferingmaterials) and reference room (painted plaster).

M. Woloszyn et al. / Building and Environment 44 (2009) 515524 517


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where r is the density of the material (kg/m3), dv is the vapour

permeability (m2/s), l is the thermal conductivity [W/(m K)], c is

the specific heat capacity of the material [J/(kg K)] and hvap is the

latent heat of vaporisation (J/kg). In the current study, the liquidflow and airflow through the envelope are neglected. This sim-

plification does not influence the result, because infiltration air-

flow is included to the overall ventilation rate and condensation

did not occur. The walls are discretised, using finite volume

method with several nodes per wall.

2.2.1.2. Simplified moisture-buffering models. Both TRNSYS versions

and Clim2000 simulation tools only compute heat transfers in

building envelope elements and use simplified models to assess

moisture-buffering capacity of materials in contact with the in-

door air. Both tools use similar types of penetration depth models

with two nodes (one for deep layer and one for surface layer) to

represent the average behaviour of room materials.

Humidity levels in materials (in deep and surface layers) arethen described using Eqs. (3) and (4):

Asurfdosurf

dt bsurfoint osurf bdeepodeep osurf, (3)

Adeepdodeep

dt bdeep;osurf odeep. (4)

In TRNSYS, moisture transfers are governed by differences in the

humidity ratio o (), and both transfer coefficients b and storage

coefficients A are computed, using materials properties for vapour

transfers and the quantity of materials in the room.

In Clim2000, only Eq. (3) is used, the differences in the

humidity ratio o () are simply replaced by differences in water

vapour density r (kg/m3) and rdeep is fixed to represent the mean

value of indoor air RH. Transfer coefficients b and storagecoefficients A were experimentally evaluated by Duforestel and

Dalicieux [38] to represent low absorption and high absorption

finishing materials and furniture.

2.2.2. Validation of simulation models: RH and energy demand with

constant ventilation rate

Even though in this study previously validated simulation tools

were used, it was necessary to validate the simulation models. The

validation was performed on a configuration very similar to the

case study analysed in this paper. Validation against experimental

data is essential, because all simulation tools are different: they

have different simulation possibilities and limitations, material

properties are defined differently, etc. In this study, simulation

tools were tested against experimental data for both test and

reference rooms (referred as run A in this study). Validation was

done as the blind test (only input parameters were given [26]).

More detailed description of the experimental data and compar-

ison between simulated and measured data can be found in Refs.

[26,27]. Fig. 4 shows an example of indoor air RH for two typicaldays. Simulation tools are able to represent correctly experimental

data; the spread between the simulated and the measured values

is in general below 10% of RH. The spread between experimental

and simulated data is always lower than 5% for CTH and lower

than 10% for UG. For the three remaining results (TTU, CETHIL and

PUCPR) the spread is lower than 10% during 95% of the time,

meaning that the difference is higher than 10% only once a day

(during the highest moisture production). This difference is the

largest for the reference room simulated by CETHIL, for minimum

and maximum values. This fact can be easily explained by the

simplified model used to represent moisture sorption by painted

plaster (envelope material directly in contact with the indoor air).

Simplified model used in Clim2000 has only two sets of default

parameters (see Section 2.2.2); which do not correspond to thematerials used in the experiment. Certainly, they can be adjusted,

ARTICLE IN PRESS

Table 2

Simulation tools and users in this study

Si mulation tool Detail ed presentation of the tool Vali dati on of the tool Institution, country

TRNSYS (version 16) [30,31] [32] UG (University of Ghent), Belgium

IDA-ICE [3335] [36,37] TTU (Tallinn University of Technology), Estonia

Clim2000 [38,39] [20,40] CETHIL (Centre de Thermique de Lyon), France

HAM-Tools [41,42] [43,44] CTH (Chalmers University), Sweden

TRNSYS (version 15) [30,31] [32] PUCPR (Pontifical Catholic University of Parana), Brazil

0

10

20

30

40

50

60

70

27/1 0:00 27/1 12:00 28/1 0:00 28/1 12:00 29/1 0:00

Relativehumidity(%)

UG PUCPR

TTU CTH

CETHIL experimental measurements

0

10

20

30

40

50

60

70

27/01 00:00 27/01 12:00 28/01 00:00 28/01 12:00 29/01 00:00

Relativehumidity(%)

UG PUCPR

TTU CTH

CETHIL experimental measurements

Fig. 4. Comparison of measured indoor RH with simulation results (left-test room, right-reference room).



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using experimental data of indoor RH. However, the results

presented here are the direct results of the blind test, without any

tuning of parameters according to monitored data.

Also, overall energy demand is simulated for both steps 1

and 2; the difference between the experimental and simulated

results is under 10% for CETHIL, TTU, PUCPR and UG, as

represented in Fig. 5.

The comparison between simulated and measured data showssatisfactory performance of simulation models. In the following,

the tools are used to perform parametric studies.

3. Results and discussion

The sets of results used in this study are presented in Table 3.

Results included calculated hourly averaged temperatures, heating

energy, RH, ventilation flow, as well as vapour flow between air

and construction for both test and reference rooms. Run A was

used for validation against the experimental data and as reference

for assessment of indoor moisture management performance. As

the computed indoor temperature was exactly equal to 20 1C for all

simulation tools, the RH was used for comparative purposes.

3.1. Impact of indoor moisture management strategies on the indoorclimate

Daily evolution of indoor RH for both ventilation systems in a

room with no hygroscopic surfaces (test room of step 1, Table 1) is

presented in Fig. 6. Clearly, the amplitude of RH variations is

smaller for RHS ventilation. Fig. 7 provides more details about the

statistical distribution of RH. It is noticeable that maximum values

are very similar for both systems, (even slightly lower for RHS

system). However, the mean and average values, as well as the

minimum values are higher for RHS system. Minimum values are

approximately 20% RH for the RHS system and go as low as 10% in

the case of constant ventilation. The target values of the indoor air

RH were between 40% and 50%, as proposed by EN 15251 [45] for

class A buildings.As shown in Fig. 8, the impact of ventilation systems is much

smaller in the mild period. The spread of RH values is still smaller

and the minimum values are higher for RHS ventilation. However,

the differences are very small, approximately 23% of RH. Both

Figs. 8 and 9 illustrate the influence of moisture-buffering on the

indoor RH. When some hygroscopic surfaces are in contact with

the indoor air, the amplitude of RH variations is much lower; it

drops approximately from 50% to 20%. This was confirmed by run

D, presented in Fig. 10 where the participants proposed some

hygroscopic materials associated with RHS ventilation. In this

case, the amplitude was less than 20%; and 50% of values were

within an interval of 8%, considered very stable. TTU and CTH used

wood to reduce very efficiently RH variations. Indeed, the

maximum spread was then 15% for TTU and 24% for CTH. PUCPR

ARTICLE IN PRESS

0

100

200

300

400

500

600

700

800

900

1000

energydemand(kWh)

STEP 1 STEP 2

experiment UG TTU CETHIL CTH PUCPR

Fig. 5. Comparison of measured heating energy use with simulation results for the

reference room and two simulation steps (step 117 days, step 234 days).

Table 3

Studied configurations and sets of results

Run A (exp./sim.) Run B (sim.) Run C (sim.) Run D (sim.) Run E (sim.)

Ventilation Constant RHS Proposed by participant RHS Proposed by participant

Indoor materials Original Original Original Proposed by participant Proposed by participant

Ste p 1 (17 /01 02/02 ) U G, TT U, CETHIL, C TH, P UCPR UG, T TU, C ETHIL , CT H, PUCPR UG, TT U, PUC PR UG, T TU UG, TT U

Step 2 (14/0219/03) UG, TTU, CETHIL, CTH, PUCPR UG, TTU, CETHIL, CTH, PUCPR UG, TTU, PUCPR UG, TTU, CTH UG, TTU

Step 3 (28/0321/04) UG, TTU, CETHIL, CTH, PUCPR UG, TTU, CETHIL, CTH, PUCPR UG, TTU, PUCPR UG, TTU, CTH, PUCPR UG, TTU, PUCPR

0

10

20

30

40

50

60

70

29/1 0:00

Relativehumidity(%)

UG PUCPR TTU CTH CETHIL

0

10

20

30

40

50

60

70

Relativehumidity(%)


27/1 0:00 27/1 12:00 28/1 0:00 28/1 12:00 29/1 0:0027/1 0:00 27/1 12:00 28/1 0:00 28/1 12:00

Fig. 6. Indoor RH in the test room computed by all participants: run A-constant ventilation rate (left) and run B-RHS ventilation (right).



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used an enlarged surface of gypsum board (which resulted in a

maximum spread of 25%), and UG used concrete to buffer

humidity variations (and obtained a maximum spread of 22%).

Additional simulations have been performed to improve the

RHS ventilation by adapting it to the outdoor climate (run C).

Indeed, run B confirmed that the indoor RH in the test room

was often below 40% because of the dry outside air in winter. For

steps 2 and 3 the indoor RH never dropped under 25%,and thus the lowest airflow rate (10 m3/h) was almost never

applied. The suggestion was to increase this lower limit to

decrease the ventilation rate in low RH regions. Finally, a

more stable indoor RH was achieved for the following schemes

(see Fig. 11):

Step 1 (cold): If the indoor RH o40%, the airflow rate is set to10m3/h, if RH 450%, it is set to 40 m3/h; in between the flow is

linearly interpolated. In this case, the humidity outside wasquite low and no buffering occurred. Not much difference in

ARTICLE IN PRESS

0

10

20

30

40

50

60

70

80

90

UG TTU CETHIL CTH PUCPR

RelativeHu

midity[%]

min - max 25-75 percentile mean median

target RH

0

10

20

30

40

50

60

70

80

90


RelativeHu

midity[%]


target RH

Fig. 7. Indoor RH in the test room during step 1 for both ventilation systems: run A-constant ventilation rate (left) and run B-RHS ventilation (right).

20

30

40

50

60

70

80

90


RelativeHumidity[%]


target RH

20

30

40

50

60

70

80

90


RelativeHumidity[%]


target RH

Fig. 8. Indoor RH during step 3 for both ventilation systems (UG, TTU and CTH include hygroscopic materials and CETHIL and PUCPR do not): run A-constant ventilation

rate (left) and run B-RHS ventilation (right).

0

10

20

30

40

50

60

70

80

90

16/04

00:00

16/04

12:00

17/04

00:00

17/04

12:00

18/04

00:00

Relativehumidity(%)


Fig. 9. Indoor RH in step 3 with (UG, CTH) and without (TTU, CETHIL, PUCPR)

additional moisture-buffering materials for constant ventilation.

20

30

40

50

60

70

80

90

UG TTU CTH PUCPR

RelativeHumidity[%]


target RH

Fig.10. Indoor RH in step 3, run D: with RHS ventilation and hygroscopic materials

proposed by the participant.



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indoor RH was noticed when applying another ventilation

scheme.

Step 2 (cold): If the indoor RH o40%, the airflow rate is set to10m3/h, if RH450%, it is set to 20 m3/h; in between the flow is

linearly interpolated. In this case the maximum ventilation

rate could be decreased because there is moisture-buffering

and the outdoor air is still quite dry.

Step 3 (mild): If the indoor RH o40%, the airflow rate is set to10m3/h, if RH450%, it is set to 50 m3/h; in between the flow is

linearly interpolated. Here again the maximum airflow rate

was increased, because of the higher indoor humidity caused

by the higher humidity of the outdoor air.

3.2. Impact of indoor moisture management strategies on energy

demand

Ventilation airflow rates for runs A and B for the test room are

compared in Fig. 12. During step 1 (cold period), the average value

of the airflow was approximately 63% of the constant ventilation

airflow rate. The differences are much less significant for the mild

period, where both mean ventilation rates are very similar. Verygood agreement between all tools on both average and amplitude

values can be seen in Fig. 12, left for step 1 with no hygroscopic

materials. Only CTH obtained larger maximum spread; however,

the maximum value represents only very few singular points

corresponding precisely to the instant when the ventilation starts,

due to a sudden peak in vapour production. The spread between

values computed by different tools is higher for step 3 ( Fig. 12,

right). This is partly explained by the fact that hygroscopic

materials were differently represented in all tools.

Energy demand is presented in Fig. 13. Ventilation systems are

compared for both average values (representing energy demand)

and maximum values (representing heating power to be in-

stalled). During the cold season (low outdoor absolute humidity,

see Fig. 13 left), reduction in energy demand is clearly identified inthe case of RHS ventilation. The energy savings computed by all

tools are between 14% and 17% of energy demand. This is directly

correlated with the reduction of the average value of fresh air

flowing into the room. However, most of the simulations predict

higher peak power (rise of as much as 8%) in the case of RHS

ventilation. This is easily explained by the sudden rise of air

change when vapour release starts, which combined with the very

cold outdoor leads to a higher heating power demand, in order to

ARTICLE IN PRESS

Fig. 11. Different RHS ventilation schemes adapted to the outdoor climate.

0

5

10

15

20

25

30

35

40

45

PUCPR

Ventilationflow[m3/h]


constant vent.

0

5

10

15

20

25

3035

40

45

Ventilationflow[m3/h]


constant vent.

UG TTU CETHIL CTH PUCPRUG TTU CETHIL CTH

Fig. 12. Computed ventilation airflow during step 1 (left) and during step 3 (right).

0

200

400

600

800

1000

1200

1400

PUCPR

Powerdemand[W]

Av. Const Max Const Av. RHS Max RHS

0

200

400

600

800

1000

1200

1400

Powerdemand[W]

Av. Const Max Const Av. RHS Max RHS

UG TTU CETHIL CTH PUCPRUG TTU CETHIL CTH

Fig. 13. Power demand for runs A and B (no hygroscopic materials) during step 1 (left) and during step 3 (right).



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maintain constant temperature. In reality, the situation might be

somewhat different, because most vapour sources are associated

with heat release (physical activity, cooking, shower, etc.).

For mild periods, the difference in energy use by both

ventilation systems is much lower (between 1% and 7%). It

confirms values from Fig. 12, right, where the average airflow

values for RHS ventilation are very similar to the constant

ventilation rate.

3.3. RH versus CO2 sensitive ventilations

IDA-ICE was used to include the effect of indoor CO2 on both

IAQ estimations and on controlling the ventilation rate. Indeed,

reducing energy used for ventilation of buildings should be made

without compromising the IAQ. Indoor CO2 levels can be used as

an indicator of the presence of human body odour and also are

often employed as an indicator to control the performance of a

ventilation system. In runs C and E, the ventilation systems with

the airflow controlled by carbon dioxide (CO2) adapt the airflow to

changes in the indoor CO2

when CO2o600 ppm, the flow is set to the minimum value ofQmin 10m

3/h,

when CO241500 ppm, the flow is set to the maximum value ofQmax 40 m

3/h, and

when CO2 is between the minimum and the maximum, theairflow rate is linearly interpolated.

According to new standard EN 15251 [45], 1200 ppm was used

as the maximum permissible indoor air CO2 content (outdoor CO2concentration was 400 ppm) for third indoor climate category.

A slightly higher limit for maximum ventilation was set to

increase the capacity of the ventilation system.The diurnal CO2 and humidity production patterns used in the

simulation tool are shown in Fig. 14. CO2 production was

calculated based on metabolic activity rate of 0.8 met during

the night and 1.2 met during peaks in the morning and the

afternoon.

The main results, presented in Table 4, were:

In the case of constant ventilation, the lowest CO2 level butalso the highest energy consumption and RH deviation were

observed.

There was similar energy consumption in the case of CO2- andRH-controlled ventilation systems, especially during cold

period (steps 1 and 2).

Hygroscopic indoor surface materials (wood fibreboard com-pared to gypsum board) damped the fluctuations of indoor RH

in all cases, irrespective of ventilation system.

During cold period, in the case of RH controlled ventilation, thelongest period when the CO2 was higher than 1200 ppm

occurred.

During warm period (step 3), both RH and CO2 controlledventilations, were keeping the CO2 levels under the limit.

During warm period (step 3), with RHS ventilation and woodfibreboard, the best stability of HR values was achieved (65% of

the time RH values were within the target interval).

4. Conclusions

This study confirmed that RHS ventilation is a good way of

reducing building energy demand in residential buildings. This

fact is directly related to the reduction of the mean ventilation

rate when the building is not used. Presented results demon-

strate that RHS ventilation reduces the spread between the

minimum and the maximum values of RH. In the tested case, it

was found that the use of a RHS system could reduce the mean

ventilation rate of 3040% in the cold period and generate 1217%

ARTICLE IN PRESS

Fig. 14. Diurnal CO2 and humidity production pattern.

Table 4

Percentage of time when the indoor climate parameters were out of the target RH (4050%) and over acceptable CO2 limit value (1200 ppm) and associated average power

demand

Run A Run B Run C Run D Run EVentilation flow Constant RH controlled CO2 controlled RH controlled CO2 controlled

Indoor surfaces Aluminium foil Gypsum board Gypsum board Wood fibreboard Wood fibreboard

Step 1 (17.012.02)

CO2 41200 ppm 0 33 0 33 0

RH out of [4050%] 84 79 80 79 80

Average power demand (W) 674 571 589 571 589

Step 2 (14.0219.03)

CO2 41200 ppm 0 35 0 45 0

RH out of [4050%] 83 65 67 57 72


Step 3 (28.0321.04)

CO2 41200 ppm 0 1 0 0 0

RH out of [4050%] 62 49 79 35 69




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of energy savings. However, during the mild period, the savings

are much lower (only about 2%), mainly because of much higher

external moisture content. It should be stressed that the energy

savings are realised while keeping the peak RH values at the

same level, therefore, without raising the risk of condensation.

This is a significant advantage of this type of demand controlled

ventilation.

However, reducing energy used for ventilation of buildingsshould be made without compromising the IAQ. For example, in

cold climates outdoor air is very dry; therefore, the indoor air is

also dry, but even then the ventilation rate cannot be too low.

Moisture production depends directly on the human activity.

Moreover, indoor CO2 levels can be used as an indicator of the

presence of human body odour. Then, the compromise could be a

combination of CO2 controlled and RH controlled ventilation

systems. Of course all other pollutants (e.g. VOCs or CO) should be

kept within correct limits. Therefore, the lower and upper limits of

ventilation rate must be carefully chosen.

This study also confirmed that the use of moisture-buffering

materials is a very efficient way to reduce the amplitude of daily

moisture variations. It was even possible, by the combined effect

of ventilation and wood as buffering material (see Fig. 10) to keepthe indoor RH at a very stable level, between 43% and 59%.

The deviation of results between different simulation tools,

remaining within a reasonable range, gives some more confidence

in the tools. Also all codes, with rather different HAM models,

proved their performance in HAM modelling of whole buildings.

Acknowledgements

This study was done within the cooperative project Annex 41

Whole Building Heat, Air and Moisture Response of the

International Energy Agencys (IEA) Energy Conservation in

Buildings and Community Systems (ECBCS) program [46]. More

details about whole building hygrothermal modelling in the IEAAnnex 41 can be found in Ref. [26]. All participants of the IEA

Annex 41 are acknowledged for their useful discussions and

remarks.

The authors gratefully acknowledge the support from Ing.

Kristin Lengsfeld from the Fraunhofer Institute for Building

Physics (IBP) in Holzkirchen, Germany, who provided the experi-

mental data needed for validation.

The authors want to thank for financial support of this study:

Brazilian Research Council (CNPq) of the Secretary for Science and

Technology of Brazil, Tallinn University of Technology (B605,

V352) and ADEME, France (Grant no. 03 04 C 0147).

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