Condensation Risk Due to Variations in Airtightness and Thermal Insulation of an Office Building in Warm and Wet Climate

Authors:

Wanghee Cho, Shizuo Iwamoto, Shinsuke Kato

Date Submitted: 2019-01-31

Keywords: warm and wet climate, office building, airtightness, thermal insulation, microbial growth, condensation risk (CR)

Abstract:

Condensation in a building encourages microbial growth, which can have an adverse effect on the health of occupants. Furthermore, it induces the deterioration of the building. To prevent problems caused by condensation, from the design step of a building, predictions of the spatial, temporal and causation for condensation occurrences are necessary. By using TRNSYS simulation coupled with TRNFLOW, condensation assessment of an entire office building in Tokyo, Japan, was conducted throughout the year, including when the air-conditioning system was not operated, by considering the absorption-desorption properties of the building materials and papers in the office and the airflow within the entire building. It was found that most of the condensation occurred during winter and was observed mainly in the non-air-conditioned core parts, especially the topmost floor. Additional analyses, which identified the effect of variations in the thermal insulation of the external walls, roof and windows and the airtightness of the windows on condensation, showed that the lower airtightness of windows resulted in decreased condensation risks, and condensation within the building was suppressed completely when the thermal insulation material thickness of the external walls was greater than 75 mm, that of the roof was greater than 105 mm and the windows had triple float glass.

Record Type: Published Article

Submitted To: LAPSE (Living Archive for Process Systems Engineering)

Citation (overall record, always the latest version): LAPSE:2019.0192 Citation (this specific file, latest version): LAPSE:2019.0192-1 Citation (this specific file, this version): LAPSE:2019.0192-1v1

DOI of Published Version: https://doi.org/10.3390/en9110875

License: Creative Commons Attribution 4.0 International (CC BY 4.0)

Article Condensation Risk Due to Variations in Airtightness and Thermal Insulation of an Ofﬁce Building in Warm and Wet Climate

Wanghee Cho 1,*, Shizuo Iwamoto 2 and Shinsuke Kato 1

1 Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan; [email protected] 2 Department of Architecture, Faculty of Engineering, Kanagawa University, 3-27-1 Rokkakubashi, Kanagawa-ku, Yokohama 221-8686, Japan; [email protected] * Correspondence: [email protected]; Tel.: +81-3-5452-6430; Fax: +81-3-5452-6432

Academic Editor: Hossam A. Gabbar Received: 5 August 2016; Accepted: 19 October 2016; Published: 27 October 2016

Abstract: Condensation in a building encourages microbial growth, which can have an adverse effect on the health of occupants. Furthermore, it induces the deterioration of the building. To prevent problems caused by condensation, from the design step of a building, predictions of the spatial, temporal and causation for condensation occurrences are necessary. By using TRNSYS simulation coupled with TRNFLOW, condensation assessment of an entire office building in Tokyo, Japan, was conducted throughout the year, including when the air-conditioning system was not operated, by considering the absorption-desorption properties of the building materials and papers in the office and the airflow within the entire building. It was found that most of the condensation occurred during winter and was observed mainly in the non-air-conditioned core parts, especially the topmost floor. Additional analyses, which identified the effect of variations in the thermal insulation of the external walls, roof and windows and the airtightness of the windows on condensation, showed that the lower airtightness of windows resulted in decreased condensation risks, and condensation within the building was suppressed completely when the thermal insulation material thickness of the external walls was greater than 75 mm, that of the roof was greater than 105 mm and the windows had triple float glass.

Keywords: condensation risk (CR); microbial growth; airtightness; thermal insulation; ofﬁce building; warm and wet climate

1. Introduction Moisture in a building directly affects an occupant’s thermal comfort and health and induces corrosion of the building. Furthermore, moisture is an essential factor for designing an air-conditioning system. Therefore, it is necessary to appropriately predict its presence and control its level. In a warm and wet climate, the most serious problems for a building caused by moisture are the ones arising from condensation. Condensation occurs when the water vapor pressure, at a certain point, exceeds the corresponding saturation vapor pressure for the temperature at that point and is classiﬁed into surface condensation and concealed condensation. Surface condensation can occur when a window has low airtightness, thereby letting outside air, which has higher humidity than inside air, enter the room in summer, while surface condensation occurs when the thermal insulation properties of a building’s outer structures, including its external walls, roof and windows, are insufﬁcient, lowering the surface temperature on the inside of the building in winter. Concealed condensation can occur when a wall has not been moisture-proofed, thereby allowing water vapor to encroach.

Energies 2016, 9, 875; doi:10.3390/en9110875 www.mdpi.com/journal/energies Energies 2016, 9, 875 2 of 25

Condensation in buildings can induce the proliferation of microorganisms, such as molds and mites. Becker [1] conducted statistical analysis on condensation and mold growth in 200 dwellings with parameters, such as location and orientation of the dwelling, occupant density and type of finishing material, and showed that mold growth occurred mainly on the thermal bridges and in dwellings with walls facing northeast to northwest, where surface condensation was observed. Using simulation, Lawton et al. [2] showed that condensation is a significant factor in mold growth in houses. Small [3] pointed out that condensation is the one cause of mold growth and emphasized that control of moisture is the essential strategy to prevent mold growth. Lengsfeld et al. [4] investigated the correlation between condensation and algae growth on outer façades and reported that microbiological growth mostly occurred on northern-oriented façades and surface condensation caused by natural long wave irradiation was the main moisture source on the façade. Pasanen et al. [5] performed field measurements and determined that condensation promotes fungal growth in ducts, especially when ventilation is turned off during nights and weekends. Fisk et al. [6], Meyer et al. [7], Bush et al. [8] and Burge et al. [9] discussed the medical effects, such as respiratory illness, asthma, allergy, fatigue, headache and cutaneous disorder, on the human body when building occupants were exposed to microbial contamination. Mendell et al. [10], Maus et al. [11], Yanagi et al. [12] and the Occupational Safety and Health Administration (OSHA) of the U.S. [13] revealed facts about the microbial contamination in air-conditioning systems. When air-conditioning units or ducts were polluted by microbes, it was possible for contaminants to be resupplied to rooms. Because the optimal growth environment (containment condition in inverse meaning) varies for each species of microbe, it is difficult to remove all microbes simultaneously and completely. In addition, if a microbe accrued in the building was not eradicated completely, its growth rate will increase rapidly when the indoor environment changes to the viable condition. Hence, it is necessary to take preventive measures to stop their initial growth. For microbes to breed, they need nutrients, air, appropriate temperature and moisture. By controlling the indoor environment at conditions that are unfavorable to microbial growth, microbial growth can be contained. However, nutrients are ubiquitous in the environment, including because of an occupant’s daily activities. In some cases, the building material itself becomes nutrients for microbes. Air is necessary for people’s survival; therefore, it also cannot be removed from the building. In addition, as room temperature in daily use (approximately 15–30 ◦C) is the most conducive temperature for the growth of microbes, it would be difficult to try to control microbes by changing the temperature of the room. As a result, controlling moisture is essential to preventing the growth of microbes in buildings. In other words, to restrain the occurrence of microbes in a building, it is important to take measures to prevent condensation. Condensation in a building induces not only harmful effects on an occupant’s health, but also the deterioration of the building, such as rottenness of wooden building materials, decreased structural capacity in timber buildings, performance degradation of thermal insulation and discoloration or exfoliation of finishing materials [14–16]. Because it is difficult to take countermeasures to resolve condensation problems after building completion, the estimation of condensation considering the building’s specifications and climate conditions is necessary from the design step of a construction process; i.e., where, when and why does condensation occur, and what can be done about it? Janssens et al. [17] evaluated condensation due to the variation in air leakage in a lightweight roof system with a 2D heat, air and vapor transfer model and emphasized increasing the thermal resistance of the roof system and enhancing the removal of vapor from the inner surface of roof system to outside. Gutt [18] examined the validity of vapor barriers in an attic as a solution to condensation, pointed out that moisture moves into the attic mainly by airflow, not by diffusion, and proposed blocking airflow from living space to the attic as an effective anti-condensation measure. Bludau et al. [19] analyzed condensation in cool roofs, identified the effect of a roof surface’s color on condensation and showed that a bright-colored roof can induce moisture accumulation in regions with very cold ambient Energies 2016, 9, 875 3 of 25 temperatures. Zillig et al. [20] and Sato et al. [21] evaluated the influence of a façade’s material type on condensation and elucidated that a façade with low thermal resistance and large thermal capacity is advantageous in terms of anti-condensation, because the heat accumulated during the day in the façade’s material and a larger scale of heat transmitted from the indoor environment reduce the effect of external night cooling. Aelemei et al. [22] investigated the effects of convection and the moisture content of outdoor air (OA) on condensation on building the façade and reported that the lower convective heat transfer coefficient of the façade, the higher the risk of surface condensation. Hien et al. [23] performed comparative analysis using computational fluid dynamics (CFD) simulation of single- and double-glazed façades in regards to energy consumption, thermal comfort and condensation and indicated that a double-glazed façade, which has the advantages of reducing the annual cooling loads and enhancing thermal comfort in the building, can promote condensation in the façade cavity, thereby requiring mechanical ventilation. Song et al. [24] conducted a case study of condensation evaluation on a double-glazed window system with an insulation spacer using 2D steady-state calculations and authenticated the effectiveness of the insulation spacer on inside surface condensation in a double-glazed window. Hamdan [25] examined condensation due to variations in insulation layer location and concluded that condensation may be decreased when the insulation layer is located at the interior side within the wall. Liu et al. [26] developed the 3D transient CFD model to estimate surface condensation on walls; the developed model can be used in the design for the position of the air inlet and the location of the exhaust fan. Ogniewicz et al. [27] analyzed condensation in porous insulation using steady-state calculations and demonstrated that condensation depends on the Péclet number, the Lewis number and the Biot number. Ge et al. [28] and Mumma [29] examined condensation in a chilled ceiling, and Muneer et al. [30] and Boyd et al. [31] developed software for evaluating condensation in buildings. Becker [32] compared the effect of heating patterns, such as intermittent or consecutive heating and the number of heating hours, on condensation, showed that consecutive heating is effective to prevent surface condensation and emphasized that the intensification of thermal insulation is essential, regardless of heating patterns. Mumovic et al. [33] evaluated the variations in condensation risk from steady-state and transient methods and indicated that the steady-state method can underestimate condensation risk, because of neglecting the diurnal fluctuations of the outdoor and indoor environmental conditions, as well as the transient response of the construction. In most of the above-mentioned studies, standard floor, restricted zone or unitary wall configurations were used to determine condensation characteristics. However, even if microbial contamination occurs due to condensation in one of those targeted places, there is still a risk that it may spread throughout the building via the air-conditioning or by the buoyancy phenomenon. There is a high risk of microbial contamination spreading through the ducts and air-conditioning systems, resupplying microbes to the rooms, thereby spreading them throughout the building, especially in buildings employing a central air-conditioning system. In addition, the thermal environments on the top floor, which is affected heavily by solar radiation and ambient air, and the first floor, which is affected by heat loss from the soil, of the building are different from those on a standard floor. Thus, the conditions for condensation and the places where it is likely to occur may also differ. Therefore, it is advisable to determine condensation occurrence for all surfaces in the entire building. Furthermore, to consider the movements of airflow in the entire building and the effect of outdoor conditions, such as wind velocity, wind direction, wind pressure due to the height from the ground surface, infiltration and exfiltration, the airflow network should be coupled with a simulation to estimate condensation. Most of the previous studies targeted specific indoor and outdoor conditions, e.g., midsummer and midwinter, and adopted steady-state simulation or short-term transient evaluation. However, when the air-conditioning system is turned off in winter, the temperatures of the wall surfaces drop, which allows condensation to form. Contrarily, in summer, condensation likely forms due to the infiltration of highly humid air from the outside. In other words, the causes of condensation vary for different seasons, making it essential to conduct evaluations throughout the year, including when the air-conditioning system is not being used. Energies 2016, 9, 875 4 of 25

Humidity fluctuation within a building is affected by the moisture adsorption-desorption properties of the building materials. Moreover, the humidity fluctuations within a room are affected greatly by the moisture adsorption-desorption of the papers kept in the room, of which there is likely to be a large quantity in an office building. It is necessary to consider the effects of their moisture adsorption-desorption when predicting humidity fluctuation in a building. Based on the preceding background, condensation risk assessment for an office building was accomplished in the present study by performing the following processes.

1 By using TRNSYS simulation, condensation conditions for all wall surfaces in an office building were investigated to identify the location(s) where condensation occurred. 2 TRNFLOW was coupled to TRNSYS simulation to take into consideration the effect of air movements on condensation, e.g., supply air (SA), return air (RA) and exhaust air (EA) of the air-conditioning system; buoyancy due to variation in temperatures; infiltration and exfiltration. 3 Condensation risks were estimated throughout the year, including when the air-conditioning system was not in operation. 4 The adsorption-desorption of building materials, including papers in office building, was estimated.

5 An index for evaluating condensation risk was proposed that utilizes the condensation ratio (CRt), condensation frequency (CFn) and condensation risk (CR). 6 Furthermore, the effect of the airtightness of the window and variations in the thermal insulation properties of the external walls, roofs and windows, which are considered to affect the occurrence of condensation, on the CR were examined, and measures to restrain building condensation were discussed.

Condensation risk estimations in an ofﬁce building were conducted under the condition of a warm and wet climate. As the representative city located in this climate, Tokyo, Japan, was selected. The detailed climate conditions of Tokyo are described in Section 2.1.1.

2. Condensation Risk Estimation under Reference Conditions In this section, condensation estimation was performed for an office building located in Tokyo, Japan, under reference conditions, which satisfied the minimum standards of airtightness and thermal insulation; mass flow coefficient = 0.000250 kg/(s·m)@1 Pa; thickness of thermal insulation (polystyrene foam type) for the external wall = 25 mm; thickness of thermal insulation (polystyrene foam type) for the roof = 50 mm; type of glass = single float.

2.1. Outline of Condensation Risk Estimation

2.1.1. Analyzed Building Characteristics Figure1a shows the standard floor plan of the analyzed building, and Figure1b shows the A-A’ sectional view. The target building characteristics, a small-to-medium sized (six-story) office building located in Tokyo with a total floor area of 3525 m2, as proposed by Yuzawa et al. [34] were adopted. Each of the rooms, as shown in the floor plan, was modeled as a zone, and the east and west staircases, elevator shaft and duct space and machine room were divided for each floor. In addition, the spaces under the floor and above the ceiling of the office each were modeled as a zone. Because of the input limitation for numbers of walls and airflows of TRNSYS and TRNFLOW, some rooms were simplified into one zone, e.g., warehouse and service room, toilets and duct space and machine room. Energies 2016, 9, 875 5 of 25 Energies 2016, 9, 875 5 of 23

28800 3600 2400 4800 3600 3600 3600 3600 3600

L4 L6 L7 L10 L12 A’ N

EV L15 Duct space L5 EA EA L16 Warehouse Machine

Elevator hall 4000 EV Service room Toilet×2 room L11

Corridor L8 L9 L3 2000

L2 3600 L13 SA

RA 20400 L14

SA=Supply air 3600

Office RA=Return air

EA=Exhaust air 3600 Crack

L1 Large opening 3600

(a) 800 4000 1500 2600 2400 800 4000 1500 2600 2400 800 4000 1500 2600 2400 24000 800 4000 1500 2600 2400 800 4000 1500 2600 2400 800 4000 1500 2600 2400 1500

(b)

FigureFigure 1.1. ((a)) StandardStandard ﬂoorfloor planplan andand airﬂowairflow networknetwork ofof thethe analyzedanalyzed building;building; ((bb)) sectionalsectional viewview (A-A’).(A‐A’). EV EV = = elevatorelevator shaft;shaft; LnLn == air linklink typetype number;number; WnWn == wall type number. Figure unit == mm.

Table 1 shows the layer composition of each component making up the roof, external wall, floor, etc., and their corresponding heat transfer coefficients (U‐factor). Table 2 shows the thermal property of each layer, e.g., thermal conductivity (W/(m∙K)); specific heat (kJ/(kg∙K)); density (kg/m3). The specifications of the external wall and roof were set in accordance with the “Method for Calculations

Energies 2016, 9, 875 6 of 25

Table1 shows the layer composition of each component making up the roof, external wall, floor, etc., and their corresponding heat transfer coefficients (U-factor). Table2 shows the thermal property of each layer, e.g., thermal conductivity (W/(m·K)); specific heat (kJ/(kg·K)); density (kg/m3). The specifications of the external wall and roof were set in accordance with the “Method for Energies 2016, 9, 875 6 of 23 CalculationsEnergies 2016 and, 9, 875 Judgements in Conformity to the 2013 Building Energy Standard of Japan,6 of 23 Part 1. Energies 2016, 9, 875 6 of 23 Non-ResidentialEnergies 2016, 9, Buildings”875 [35]. The thickness of the thermal insulation materials (polystyrene6 of 23 foam Energiesand Judgements 2016, 9, 875 in Conformity to the 2013 Building Energy Standard of Japan, Part6 of 231. and Judgements in Conformity to the 2013 Building Energy Standard of Japan, Part 1. type)andNon was ‐ResidentialJudgements set to 25 mm Buildings” in for Conformity the [35]. external The to thickness wallthe and2013 of the 50Building mmthermal for Energyinsulation the roof Standard (see materials Table of (polystyrene 12Japan,). Furthermore, Part foam 1. a andNon ‐ResidentialJudgements Buildings” in Conformity [35]. The to thickness the 2013 of theBuilding thermal Energyinsulation Standard materials of (polystyrene Japan, Part foam 1. plan whereandNontype) ‐Residential Judgementswas the set external to 25Buildings” inmm wall Conformity for was the[35]. pasted external The to thickness onthe wall the 2013 and outer of the50Building surface mmthermal for of Energytheinsulation the roof pillars (seeStandard materials Table was assumed,12).of (polystyrene Japan,Furthermore, andPart foam thus, 1.a the Nontype)‐Residential was set to 25Buildings” mm for the[35]. external The thickness wall and of the50 mmthermal for theinsulation roof (see materials Table 12). (polystyrene Furthermore, foam a effectsNontype)plan of‐ aResidentialwhere was thermal set the to bridgeexternal 25Buildings” mm were forwall the[35]. was not external The considered.pasted thickness wall on the and of The outer the50 glazing mmthermal surface for the ofinsulation of windows roofthe pillars (see materials Table was was setassumed,12). (polystyrene as Furthermore, single and float foamthus, a glass type)plan where was set the to external 25 mm forwall the was external pasted wall on the and outer 50 mm surface for the of roofthe pillars (see Table was assumed,12). Furthermore, and thus, a (see Tabletype)planthe effects where 13was). The setof the ato ratio thermalexternal 25 mm of thebridge forwall areathe was wereexternal on pasted thenot wall façadesconsidered. on the and outer occupied50 Themm surface glazingfor by the of windows rooftheof windows pillars (see Table was was was 20.8%. assumed,12). set Furthermore, as single and thus,float a planthe effects where of the a thermalexternal bridge wall was were pasted not considered. on the outer The surface glazing of theof windows pillars was was assumed, set as single and thus,float plantheglass effects where(see Table of the a thermal external13). The bridge wallratio wasof were the pasted areanot considered.on on the the façades outer The surface occupied glazing of thebyof windows windowspillars was waswas assumed, set20.8%. as single and thus,float theglass effects (see Table of a thermal 13). The bridge ratio of were the areanot considered.on the façades The occupied glazing byof windowswindows waswas set20.8%. as single float theglass effects (see Table of a thermal 13). The bridge ratio of were the areanot considered.on the façades The occupied glazing byof windowswindows waswas set20.8%. as single float glass (see TableTable 13). 1. TheHeat ratio transfer of the coefficient area on the and façades layer occupied composition by windows of each wall was type. 20.8%. glass (see Table 13).Table The 1. ratioHeat transferof the area coefficient on the and façades layer occupiedcomposition by of windows each wall wastype. 20.8%. Table 1. Heat transfer coefficient and layer composition of each wall type. Wall Type (Wall TypeTable Number 1. Heat1) (Heat transfer coefficientLayer and Composition layer composition (from Inner of Side each to wall Outer type. Side in the Zone), Wall TypeTable (Wall 1.Type Heat Number transfer 1) coefficientLayer and Composition layer composition (from Inner of each Side wall to Outer type. Side in the Zone), Transfer CoefficientWall Type (U-Factor)Table (Wall 1.Type (W/(m Heat Number2 transfer·K)) 1) coefficientLayer and Composition layer composition(Layer (from Thickness Inner of each Side (mm)) wall to Outer type. Side in the Zone), (Heat Transfer Coefficient (U‐Factor) (W/(m1 2∙K)) (Layer Thickness (mm)) (Heat TransferWall Type Coefficient (Wall Type (U‐ Factor)Number (W/(m ) 2∙K)) Layer Composition (from(Layer Inner Thickness Side to (mm)) Outer Side in the Zone), (Heat TransferWall Type Coefficient (Wall Type (U‐ Factor)Number (W/(m 1) ∙K)) Layer Composition (from(Layer Inner Thickness Side to (mm)) Outer Side in the Zone), (Heat TransferWall Type Coefficient (Wall Type (U‐ Factor)Number (W/(m 1) 2∙K)) Layer Composition (from(Layer Inner Thickness Side to (mm)) Outer Side in the Zone), (Heat Transfer Coefficient (U‐Factor) (W/(m2∙K)) (Layer Thickness (mm)) (Heat Transfer Coefficient (U‐Factor) (W/(m2∙K)) Concrete(Layer Thickness (150),Concrete cement (mm)) (150), mortar cement (15), mortar (15), Concrete (150), cement mortar (15), waterproofingwaterproofing layer (asphalt layer type, (asphalt 5), cement type, 5), Roof (W1)Roof (0.611) (W1) (0.611) waterproofingConcrete (150),cement layer cement mortar (asphalt mortar (15), type, (15), thermal 5), cement insulation Roof (W1) (0.611) Concretemortar (15), (150), thermal cement insulation mortar (15), material Concretemortarwaterproofing (15), (150),material thermal layercement (polystyrene (asphaltinsulation mortar type, (15), material foam 5), cement type, 50), Roof (W1) (0.611) waterproofingmortar (15), thermal layer (asphaltinsulation type, material 5), cement Roof (W1) (0.611) waterproofing(polystyrenemortar (15),concrete thermal foam layer type, (60) (asphaltinsulation 50), concrete type, material 5), (60)cement Roof (W1) (0.611) mortar(polystyrene (15), thermal foam type, insulation 50), concrete material (60) mortar(polystyrene (15), thermal foam type, insulation 50), concrete material (60) (polystyrene foam type, 50), concrete (60) Ceiling (W2) (2.702) (polystyreneAcoustic board foam (12), type, gypsum 50), concrete board (10) (60) CeilingCeiling (W2) (2.702) (W2) (2.702) Acoustic boardAcoustic (12), boardgypsum (12), board gypsum (10) board (10) RaisedCeiling floor(W2) (W3) (2.702) (3.846) CarpetAcoustic (3), board aluminum (12), gypsum type plate board (10) (10) RaisedCeilingRaised floor (W3) floor(W2) (3.846) (W3) (2.702) (3.846) AcousticCarpet (3), board aluminumCarpet (12), (3), gypsum type aluminum plate board (10) type (10) plate (10) CeilingRaised floor(W2) (W3) (2.702) (3.846) AcousticCarpet (3), board aluminum (12), gypsum type plate board (10) (10) Raised floor (W3) (3.846) Carpet (3), aluminum type plate (10) RaisedFloor (W4) floor (3.608) (W3) (3.846) CarpetConcrete (3), (150) aluminum type plate (10) Floor (W4) (3.608) Concrete (150) Floor (W4)Floor (3.608) (W4) (3.608) Concrete (150)Concrete (150) Floor (W4) (3.608) Concrete (150) Floor (W4) (3.608) Concrete (150) Gypsum board (8), non‐closed air layer (–) 2, Gypsum board (8), non‐closed air layer (–) 2, thermalGypsum insulation board (8), materialnon‐closed air layer (–) 2, External wall (W5) (0.519) Gypsumthermal insulation board (8), materialnon‐closed air layer (–) 2, External wall (W5) (0.519) Gypsum(polystyrenethermal insulation boardGypsum foam (8), type,materialnon board‐ closed25), (8), concrete non-closedair layer (150), (–) air 2, layer External wall (W5) (0.519) thermal(polystyrene insulation(–) foam2, thermal type,material 25), insulation concrete material (150), ExternalExternal wall (W5) wall (0.519) (W5) (0.519) thermalcement(polystyrene mortarinsulation foam (25), type,material tile (10) 25), concrete (150), External wall (W5) (0.519) (polystyrenecement mortar(polystyrene foam (25), type, tile (10) foam25), concrete type, 25), (150), concrete (polystyrenecement mortar foam (25), type, tile (10)25), concrete (150), cement mortar(150), (25), cement tile (10) mortar (25), tile (10) cement mortar (25), tile (10)

Gypsum board (24), non‐closed air layer (–) 2, Internal wall (W6) (3.343) Gypsum board (24), non‐closed air layer (–) 2, Internal wall (W6) (3.343) gypsumGypsum boardboard (24)(24), non‐closed air layer (–) 2, Internal wall (W6) (3.343) Gypsumgypsum boardboard (24)(24), non‐closed air layer (–) 2, Internal wall (W6) (3.343) Gypsumgypsum boardboardGypsum (24)(24), boardnon‐closed (24), non-closedair layer (–) air 2, layer InternalInternal wall (W6) wall (3.343) (W6) (3.343) gypsum board (24) gypsum board(–) 2 (24), gypsum board (24) 1 See Figure 1b for the numbers of the corresponding wall types; 2 the thermal property of the non‐ 1 See Figure 1b for the numbers of the corresponding wall types; 2 the thermal property of the non‐ 1 2 closed See Figure air layer 1b forwas the set numbersas thermal of resistancethe corresponding (=0.07 (m 2wall∙K)/W). types; the thermal property of the non‐ 1closed See Figure air layer 1b forwas the set numbersas thermal of resistancethe corresponding (=0.07 (m 2wall∙K)/W). types; 2 the thermal property of the non‐ 1 See1closed See Figure Figure air1b layer for 1b the forwas numbers the set numbersas thermal of the of corresponding resistancethe corresponding (=0.07 wall (m types; 2wall∙K)/W). types;2 the thermal2 the thermal property property of the of non-closed the non‐ air closed air layer was set as thermal resistance (=0.07 (m2∙K)/W). layerclosed was set air as layer thermal was resistanceset as thermalTable (=0.07 2.resistance Thermal (m2·K)/W). (=0.07property (m2 of∙K)/W). each wall layer. Table 2. Thermal property of each wall layer. Table 2. Thermal property of each wall layer. Material of Layer ThermalTable Conductivity 2. Thermal property(W/(m∙K)) of eachSpecific wall layer.Heat (kJ/(kg∙K)) Density (kg/m3) Material of Layer ThermalTable Conductivity 2. Thermal property(W/(m∙K)) of eachSpecific wall layer.Heat (kJ/(kg∙K)) Density (kg/m3) MaterialConcrete of Layer ThermalTable Conductivity 2. Thermal1.40 property (W/(m∙K)) of eachSpecific wall Heat layer.0.88 (kJ/(kg ∙K)) Density2200 (kg/m 3) MaterialConcrete of Layer Thermal Conductivity1.40 (W/(m∙K)) Specific Heat0.88 (kJ/(kg ∙K)) Density2200 (kg/m 3) MaterialCementConcrete ofmortar Layer Thermal Conductivity1.401.5 (W/(m∙K)) Specific Heat0.800.88 (kJ/(kg ∙K)) Density20002200 (kg/m 3) CementConcrete mortar 1.401.5 0.880.80 22002000 3 MaterialWaterproofingCementConcrete of Layer mortar layer Thermal Conductivity0.1101.401.5 (W/(m·K)) Speciﬁc Heat0.880.800.92 (kJ/(kg ·K)) Density220020001000 (kg/m ) WaterproofingCement mortar layer 0.1101.5 0.800.92 20001000 WaterproofingPolystyreneConcreteCement mortar foam layer 1.400.1100.0401.5 0.800.921.13 0.88 2000100020 2200 WaterproofingPolystyrene foam layer 0.1100.040 0.921.13 100020 CementWaterproofingPolystyreneAcoustic mortar board foam layer 1.50.1100.0400.064 0.921.130.84 0.80 100030020 2000 PolystyreneAcoustic board foam 0.0400.064 1.130.84 30020 WaterprooﬁngPolystyreneAcousticGypsum layer board foam 0.1100.0400.0640.70 1.130.84 0.921.0 30091020 1000 AcousticGypsum board 0.0640.70 0.841.0 300910 PolystyreneAcousticGypsumCarpet foam board 0.0400.0640.0800.70 0.840.80 1.131.0 300910400 20 GypsumCarpet board 0.0800.70 0.801.0 910400 AcousticAluminumGypsumCarpet board type board plate 0.0640.080210.00.70 0.800.88 0.841.0 2700910400 300 GypsumAluminumCarpet board type plate 0.700.080210.0 0.800.88 1.0 2700400 910 AluminumCarpetTile type plate 0.080210.01.30 0.800.880.84 27002400400 AluminumCarpetTile type plate 0.080210.01.30 0.880.84 0.80 27002400 400 AluminumTile type plate 210.01.30 0.880.84 27002400 Aluminum typeTile plate 210.01.30 0.84 0.88 2400 2700 TheTile standardTile year weather data 1.30 1.30of the extended AMeDAS (Automated0.84 Meteorological2400 2400 Data The standard year weather data of the extended AMeDAS (Automated Meteorological Data AcquisitionThe standard System) year (1981–2000) weather fordata Tokyo of the [36] extended was used. AMeDAS Figure (Automated2 shows the annualMeteorological outdoor Datadry‐ AcquisitionThe standard System) year (1981–2000) weather fordata Tokyo of the [36] extended was used. AMeDAS Figure (Automated2 shows the annualMeteorological outdoor Datadry‐ Acquisitionbulb Thetemperature standard System) (°C)year (1981–2000) and weather humidity fordata Tokyo ratioof the [36](kg/kg extended was dry used. AMeDASair Figure(DA)) of(Automated2 showsTokyo. the The annualMeteorological ranges outdoor of outdoor Datadry‐ TheAcquisitionbulb standardtemperature System) year (°C) (1981–2000) weather and humidity data for Tokyo of ratio the [36](kg/kg extended was dry used. AMeDASair Figure(DA)) of2 (Automated showsTokyo. the The annual ranges Meteorological outdoor of outdoor dry‐ Data Acquisitionbulbdry‐bulb temperature temperature System) (°C) (1981–2000) andand thehumidity humidity for Tokyo ratio ratio [36](kg/kg of was each dry used. air ‐Figureconditioning(DA)) of2 showsTokyo. period the The annual are ranges summarized outdoor of outdoor dry in‐ bulbdry‐bulb temperature temperature (°C) andand thehumidity humidity ratio ratio (kg/kg of each dry air ‐conditioning(DA)) of Tokyo. period The are ranges summarized of outdoor in AcquisitionbulbdryTable‐bulb temperature 3. System) Thetemperature maximum (1981–2000) (°C) andand outdoor thehumidity for humidity Tokyotemperature ratio [ 36ratio (kg/kg] was andof each used. drythe meanair Figure ‐conditioning(DA)) outdoor2 showsof Tokyo. temperature period the The annual are ranges aresummarized outdoor 34.4 of outdoor °C dry-bulb and in dryTable‐bulb 3. The◦temperature maximum and outdoor the humidity temperature ratio andof each the meanair‐conditioning outdoor temperature period are aresummarized 34.4 °C and in temperaturedryTable16.6‐ bulb°C. 3. ( ThetemperatureC) maximum and humidity and outdoor the ratio humidity temperature (kg/kg ratio dry andof air each the (DA)) meanair‐ ofconditioning outdoor Tokyo. Thetemperature period ranges are of aresummarized outdoor 34.4 °C dry-bulband in Table16.6 °C. 3. The maximum outdoor temperature and the mean outdoor temperature are 34.4 °C and Table16.6 °C. 3. The maximum outdoor temperature and the mean outdoor temperature are 34.4 °C and 16.6 °C. 16.6 °C.

Energies 2016, 9, 875 7 of 25 temperature and the humidity ratio of each air-conditioning period are summarized in Table3. ◦ ◦ TheEnergies maximum 2016, 9, 875 outdoor temperature and the mean outdoor temperature are 34.4 C and 16.6 C.7 of 23

■Outdoordry-bulb temperature ■Outdoor humidity ratio 40 0.05

30 0.04

20 0.03

10 0.02

0 0.01 Outdoor dry-bulb temperature (ºC) temperature dry-bulb Outdoor -10 0 DA) (kg/kg ratio humidity Outdoor 123456789101112 Month Figure 2. Annual outdoor dry-bulbdry‐bulb temperature and humidity ratio ofof Tokyo.Tokyo. DA,DA, drydry air.air.

Table 3.3. RangeRange ofof outdooroutdoor dry-bulbdry‐bulb temperaturetemperature andand humidityhumidity ratioratio inin eacheach period.period. Cooling Period Intermediate Periods Heating Period Intermediate Periods (June–September)Cooling Period (April–May and October–November) (December–March)Heating Period (April–May and Dry‐(June–September)bulb Humidity ratio Dry‐bulb Humidity ratio Dry(December–March)‐bulb Humidity ratio October–November) temperature (°C) (kg/kg DA) temperature (°C) (kg/kg DA) temperature (°C) (kg/kg DA) Dry-bulb14.4~34.4 Humidity0.0077~0.0204 ratio −Dry-bulb0.5~22.9 Humidity0.0010~0.0120 ratio Dry-bulb4.7~28.4 Humidity0.0017~0.0174 ratio temperature (◦C) (kg/kg DA) temperature (◦C) (kg/kg DA) temperature (◦C) (kg/kg DA) 14.4~34.4 0.0077~0.0204 −0.5~22.9 0.0010~0.0120 4.7~28.4 0.0017~0.0174 There was an underground pit 1.5 m deep underneath the first floor, and its external walls were set to be in contact with the ground. The ground temperature was calculated using Kusuda’s calculationThere was method an underground [37,38]. In Equation pit 1.5 m deep(1), mean underneath ground the temperature first floor, and (it was its external substituted walls by were using set tothe be mean in contact annual with ambient the ground. air temperature) The ground temperature Tmean (=16.6 was °C), calculated amplitude using of Kusuda’ssurface temperature calculation method(maximum [37 ,38air]. temperature—minimum In Equation (1), mean ground air temperature) temperature T (itamp was (=17.8 substituted °C) and by day using of thethe mean year ◦ annualcorresponding ambient to air the temperature) minimum surfaceTmean (=16.6temperatureC), amplitude tshift (= 52) of were surface calculated temperature based on (maximum the weather air ◦ temperature—minimumdata [36]. Thermal diffusivity air temperature) of the groundT amp(soil)(=17.8 α [39]C) was and set day to 1.4 of the× 10 year−3 m2/h. corresponding to the minimum surface temperature tshift (= 52) were calculated based on the weather data [36]. Thermal 0.5 0.5 diffusivity of the ground (soil) α [39] was set  to 1.4× 10−23m2/h. D  365    Tground  Tmean  Tamp exp  D   cos  t now  t shift     (1)   365    365  2     " ( )# Figure 3 shows the results from calculating πα 0.5 the ground2π temperature at Da depth 365α of 0.51.5 m and at T = T − T exp −D cos t − t − (1) the groundground surfacemean (depthamp = 0 m). The ground365 temperature365 atnow a depthshi fof t 1.52 m wasπ lowest in early April due to the influence of the phase delay. Figure3 shows the results from calculating the ground temperature at a depth of 1.5 m and at the 40 ground surface (depth = 0 m). The ground temperature at a depth of 1.5 m was lowest in early April due to the influence of the phase30 delay. Ground surface 20 Depth=1.5 m 10

0 Ground temperature (ºC)

-10 1 234 5 6 7 8 9 10 11 12 Month Figure 3. Ground temperature at a depth of 1.5 m and at the ground surface.

Energies 2016, 9, 875 7 of 23

■Outdoordry-bulb temperature ■Outdoor humidity ratio 40 0.05

30 0.04

20 0.03

10 0.02

0 0.01 Outdoor dry-bulb temperature (ºC) temperature dry-bulb Outdoor -10 0 DA) (kg/kg ratio humidity Outdoor 123456789101112 Month Figure 2. Annual outdoor dry‐bulb temperature and humidity ratio of Tokyo. DA, dry air.

Table 3. Range of outdoor dry‐bulb temperature and humidity ratio in each period.

Cooling Period Intermediate Periods Heating Period (June–September) (April–May and October–November) (December–March) Dry‐bulb Humidity ratio Dry‐bulb Humidity ratio Dry‐bulb Humidity ratio temperature (°C) (kg/kg DA) temperature (°C) (kg/kg DA) temperature (°C) (kg/kg DA) 14.4~34.4 0.0077~0.0204 −0.5~22.9 0.0010~0.0120 4.7~28.4 0.0017~0.0174

There was an underground pit 1.5 m deep underneath the first floor, and its external walls were set to be in contact with the ground. The ground temperature was calculated using Kusuda’s calculation method [37,38]. In Equation (1), mean ground temperature (it was substituted by using the mean annual ambient air temperature) Tmean (=16.6 °C), amplitude of surface temperature (maximum air temperature—minimum air temperature) Tamp (=17.8 °C) and day of the year corresponding to the minimum surface temperature tshift (= 52) were calculated based on the weather data [36]. Thermal diffusivity of the ground (soil) α [39] was set to 1.4 × 10−3 m2/h.

0.5 0.5       2  D  365    Tground  Tmean  Tamp exp  D   cos  t now  t shift     (1)   365    365  2    

Figure 3 shows the results from calculating the ground temperature at a depth of 1.5 m and at Energiesthe ground2016, 9 surface, 875 (depth = 0 m). The ground temperature at a depth of 1.5 m was lowest in 8early of 25 April due to the influence of the phase delay.

30 Ground surface 20 Depth=1.5 m 10

0 Ground temperature (ºC)

-10 1 234 5 6 7 8 9 10 11 12 Month Figure 3. Ground temperature at a depth of 1.5 m and at the ground surface. Figure 3. Ground temperature at a depth of 1.5 m and at the ground surface.

2.1.2. Internal Conditions in the Building The air-conditioning on/off time, the internal heat generations, occupant density and air volume for ventilation were set based on the “Method for Calculations and Judgements in Conformity to the 2013 Building Energy Standard of Japan, Part 1. Non-Residential Buildings” [35]. Table4 shows the air-conditioning period and each air-conditioning setting in an ofﬁce. The air-conditioning system was operated from 7 a.m.–9 p.m. (preheating and precooling from 7 a.m.–8 a.m. and sensible heat load processing only for the ofﬁces) and only on weekdays, not on weekends or holidays.

Table 4. Air-conditioning setting in an ofﬁce.

Intermediate Periods Summer (Cooling Period) Winter (Heating Period) (April–May and (June–September) (December–March) October–November) Dry-bulb Relative Dry-bulb Relative Dry-bulb Relative temperature (◦C) humidity (%) temperature (◦C) humidity (%) temperature (◦C) humidity (%) 26 50 24 50 22 50

The heat generated from the lighting and ofﬁce application each was set at 12 W/m2 and the occupant density at 0.1 person/m2, and these were multiplied by the ratios shown in Table5. In addition, the ratios of heat generation from ofﬁce appliances on weekends and holidays were set at 25% as a standby power condition. Based on the “Handbook of the Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, Vol. 1 Fundamental” [40], the heat generated by a human body was set to be 121 W/m2, which was determined by dividing the proportion of sensible heat and latent heat for each set air-conditioning temperature. Table6 shows heat generation from the human body by air-condition usage period. Furthermore, when calculating the water vapor emitted, only that generated by a human body was included, and the water vapor from the service rooms or toilets was not considered.

Table 5. Ratio of internal heat generation.

Time (h) 1 2 3 4 5 6 7 8 9 10 11 12 Lighting (%) 0 0 0 0 0 0 0 0 100 100 100 100 Ofﬁce appliance (%) 25 25 25 25 25 25 25 25 100 100 100 100 Occupancy (%) 0 0 0 0 0 0 0 0 100 100 100 100 Energies 2016, 9, 875 9 of 25

Table 5. Cont.

Time (h) 13 14 15 16 17 18 19 20 21 22 23 24 Lighting (%) 50 100 100 100 100 100 100 100 80 0 0 0 Ofﬁce appliance (%) 80 100 100 100 100 100 100 50 50 25 25 25 Occupancy (%) 60 100 100 100 100 100 50 30 20 0 0 0

Table 6. Heat generation from a human body in an ofﬁce.

Cooling Period Intermediate Periods Heating Period (June–September) (April–May and October–November) (December–March) Sensible heat (W) Latent heat (W) Sensible heat (W) Latent heat (W) Sensible heat (W) Latent heat (W) 68 53 73 48 78 43

The air volume of ventilation in the offices was set as 5 m3/(m2·h). The ventilation in the toilets and warehouse/service room was set to occur at an air change rate (ACH) of five per hour, and part of the EA from the office was supplied via the corridor.

2.1.3. Airflow Network in the Building The airflow networks for the standard floor plan were set as shown in Figure1a, and Table7 shows the air link types, from node to node, the areas of openings, the lengths of cracks, mass flow coefficients and airflow rate exponents. The airflow rate exponent of the window was set to one, in accordance with Japanese Industrial Standard (JIS) A 4706 [41]. The airflow rate exponent and mass flow coefficients of other air links were set to 0.6, based on the TRNFLOW manual [42]. In this study, not only the airflows of the plane, but also the airflows above and below the staircases and EV shafts were considered. An opening was classified as a large opening (LO) or crack according to TRNFLOW [42]. The doors of the offices had a door louver (600 mm × 300 mm, aperture ratio 40%), and the doors of the toilets, warehouses and service rooms had an undercut of 0.01 m. The door louvers and undercuts were classified as LOs, and the other gaps in the doors and windows were classified as cracks. The airtightness of a window was given an A-2 grade (for general building) as stipulated in JIS A 4706 [41] (see Table 11). To consider the airflow within the building through the air-conditioning system, airflow networks, including SA, RA and EA of the air-conditioning system, were established as shown in Figure1a. The SA and RA were set on the office ceiling, whereas the EA was set on the ceilings of the toilets and warehouses/service room zones. The SA was modeled with a fan, auxiliary node and duct according to TRNFLOW [42]. Airflow rate, dry-bulb temperature and relative humidity of the SA were calculated every hour, as explained below in Section 2.1.4. The fan was modeled to blow out this air volume, and the auxiliary node was used to define the temperature and humidity of the SA. In addition, the RA air volume was set with the fan, and the RA air volume in the office became the difference in the airflow rates of the SA in the office and the ventilation in the toilets and warehouse/service room zones. Table8 shows the wind pressure coefficient according to wind angle for each of the building’s walls. Values that were interpolated linearly depending on the wind direction, by diverting the wind pressure coefficient of the eight directions used in a three-story square plane building located in a shielded area according to Table A3 of the TRNFLOW manual appendix [42], were used as the wind pressure coefficients. As the wind pressure coefficient value in the shielded category assumes that the surroundings are enclosed with buildings of the same type, its value is small as compared to the general single-structure locations. Furthermore, the wind pressure coefficient was set uniform, and its surface distribution was not considered. Energies 2016, 9, 875 10 of 25

Table 7. Setup of airﬂow links in standard ﬂoor. OA = outdoor air; SA = supply air; RA = return air; EA = exhaust air.

Air link Number 1 From Node To Node Air Link Type Characteristics of the Link 1 OA (south) Office Crack Length of crack = 80 m; mass flow coefficient = 0.00025 kg/(s·m)@1 Pa; airflow exponent = 0.6 Door louver; area of opening = 0.6 m (W) × 0.3 m (H); number of openings = 4; opening rate = 40 2 Office Corridor Large opening %; airflow exponent = 0.6 3 Elevator hall/corridor Staircase (west) Crack Length of crack = 9.6 m; mass flow coefficient = 0.0000130 kg/(s·m)@1 Pa; airflow exponent = 0.6 4 Staircase (west) OA (north) Crack Length of crack = 6.4 m; mass flow coefficient = 0.00025 kg/(s·m)@1 Pa; airflow exponent = 1 5 Elevator hall/corridor Elevator shaft Crack Length of crack = 18 m; mass flow coefficient = 0.0000130 kg/(s·m)@1 Pa; airflow exponent = 0.6 6 Elevator hall/corridor OA (north) Crack Length of crack = 6.4 m; mass flow coefficient = 0.00025 kg/(s·m)@1 Pa; airflow exponent = 1 7 Warehouse/service room OA (north) Crack Length of crack = 6.4 m; mass flow coefficient = 0.00025 kg/(s·m)@1 Pa; airflow exponent = 1 Undercut of door; area of undercut = 2 m (W) × 0.01 m (H); number of undercuts = 1; airflow 8 Elevator hall/corridor Warehouse/service room Large opening exponent = 0.6 Undercut of door; area of undercut = 0.9 m (W) × 0.01 m (H) ; number of undercuts = 2; airflow 9 Elevator hall/corridor Toilet Large opening exponent = 0.6 10 Toilet OA (north) Crack Length of crack = 12.8 m; mass flow coefficient = 0.00025 kg/(s·m)@1 Pa; airflow exponent = 1 11 Elevator hall/corridor Staircase (east) Crack Length of crack = 9.6 m; mass flow coefficient = 0.0000130 kg/(s·m)@1 Pa; airflow exponent = 0.6 12 Staircase (east) OA (north) Crack Length of crack = 6.4 m; mass flow coefficient = 0.00025 kg/(s·m)@1 Pa; airflow exponent = 1 SA; dry-bulb temperature, humidity ratio and airflow rate of SA were set according to the 13 Auxiliary node Office Duct calculation method described in Section 2.1.4 14 Office Auxiliary node Fan RA; airflow rate = airflow rate of SA − airflow rate of EA 15 Warehouse/service room Auxiliary node Fan EA; airflow rate = 5 ACH 16 Toilet Auxiliary node Fan EA; airflow rate = 5 ACH 1 See Figure1a for the numbers of the corresponding air links. Energies 2016, 9, 875 11 of 25

Table 8. Wind pressure coefﬁcient according to wind angle.

Wall Wind Angle (South = 0◦, West = 90◦, North = 180◦, East = 270◦) Orientation 0◦ 45◦ 90◦ 135◦ 180◦ 225◦ 270◦ 315◦ South 0.2 0.05 −0.25 −0.3 −0.25 −0.3 −0.25 0.05 West −0.25 0.05 0.2 0.05 −0.25 −0.3 −0.25 −0.3 North −0.25 −0.3 −0.25 0.05 0.2 0.05 −0.25 −0.3 East −0.25 −0.3 −0.25 −0.3 −0.25 0.05 0.2 0.05

2.1.4. Supply Air Condition of Air-Conditioning The air-conditioning system was set as a single duct variable air volume (VAV) system. The SA condition was modeled based on the load calculation results. Using the sensible-heat load for every hour in the ofﬁces on every ﬂoor, the SA air volume VSA was calculated using Equation (2).

qSH VSA = (2) cAρA∆TO f f ice_SA The SA temperature and humidity conditions during the cooling period were 16 ◦C and 90%, respectively, and any OA introduced above the minimum volume (= 2073.6 m3/(h·floor)) was always blown out. For all of the offices on Floors 1–6, when the minimum volume of OA was introduced, the SA temperature was calculated backward from Equation (2). The humidity ratio at this time adopted the small value of water vapor from the relative humidity of 90% and the outlet of the enthalpy ◦ recovery ventilator (ERV). The outlet temperature ( C) of ERV TERV was calculated from Equation (3) and the humidity ratio (kg/kg DA) of the ERV XERV from Equation (4). Both the sensible-heat exchange efficiency ηSH (–) and the latent-heat exchange efficiency ηLH (–) of the ERV were set as 0.7.

TERV = TOA − ηSH(TRA − TOA) (3)

XERV = XOA − ηLH(XRA − XOA) (4) For the heating period, the SA volume was calculated from Equation (2), setting the difference in ◦ temperature between the office and SA ∆TOffice_SA to be 10 C. Furthermore, using the latent-heat load of the office, the SA humidity ratio XSA_Humid (kg/kgDA) was calculated from Equation (5).

qLH XSA_Humid = XSP_Humid − (5) ρA LVSA

2.1.5. Moisture Adsorption-Desorption of Building Materials The Buffer Storage Humidity Model (Moisture Capacitance Model) [43–47] of TRNSYS was used to calculate the moisture adsorption-desorption of the building materials. This model can be used to calculate the moisture migration between the zone and the surface of a building material and between the surface of a building material and the deep portions of a building material (Figure4). In Equation (6), the zone humidity was calculated, considering the exchange of moisture between the zone node and the surface storage. The dynamics of the water content of the surface storage and deep storage were calculated using Equations (7) and (8), respectively. Not only was the moisture adsorption-desorption of the building materials considered, but also that of the papers in the offices. The amount of papers stored inside the offices was quoted from actual survey results [48] and set to 5.7 fm/person. The unit fm means the height (m: meter) of the cumulated A4 size (210 mm × 297 mm) papers. Because the maximum number of occupant in this office building is 41 persons/floor, the total amount of papers is 14.60 m3/floor. The total surface area of papers was calculated assuming that papers occupied 25% of the desk surface area. These papers were modeled as one part of the walls in the simulations. Table9 shows the moisture adsorption-desorption property of the building materials, as well as one piece of paper. These properties were set based on the Energies 2016, 9, 875 11 of 23

X ERV  XOA LH (X RA  XOA) (4)

For the heating period, the SA volume was calculated from Equation (2), setting the difference Energiesin temperature2016, 9, 875 between the office and SA ΔTOffice_SA to be 10 °C. Furthermore, using the latent12‐heat of 25 load of the office, the SA humidity ratio XSA_Humid (kg/kgDA) was calculated from Equation (5).

Japanese database (materials) in WUFI pro 4.2. The values in databaseq were estimated by Japan Testing X  X  LH Center for Construction Materials (JTCCM).SA _ Humid AdsorptionSP _ Humid isotherms of the database were measured(5)  ALVSA under the condition that the temperature in the desiccator was controlled at 23 ◦C, according to JIS A 1475 [49]. Assuming that indoor relative humidity was in the range of 40%–60%, the gradients of 2.1.5.sorptive Moisture isothermal Adsorption lines in‐Desorption Table9 were of calculated Building Materials from the gradient of the straight line connecting two moistureThe Buffer contents Storage ((kg Humidity (water)/kg Model (building (Moisture material)) Capacitance of relative Model) humidity [43–47] of of TRNSYS 40% and was 60% used on toadsorption calculate isotherms.the moisture The adsorption adsorption‐desorption process and of the desorption building processmaterials. have This different model can curves be used on the to calculateadsorption the isotherm; moisture migration this characteristic between isthe called zone and hysteresis. the surface However, of a building the adsorption-desorption material and between thecalculation surface in of the a Bufferbuilding Storage material Humidity and the Model deep uses portions the same of curves. a building In other material words, the(Figure desorption 4). In processEquation is (6), treated the zone as the humidity adversarial was process calculated, of adsorption. considering The the ﬂuctuations exchange ofof adsorption-desorptionmoisture between the zonedue to node variations and the in surface indoor storage. air temperature The dynamics and building of the water material’s content temperature of the surface are notstorage considered and deep in storagethe Buffer were Storage calculated Humidity using Model. Equations (7) and (8), respectively.

Zone node Surface storage Deep storage

Gradient of sorptive Gradient of sorptive isothermal line isothermal line

κsurf κdeep

Mass of material Mass of material

Msurf Mdeep βsurf βdeep

Figure 4. Conceptual diagram of the Buffer Storage Humidity Model. Figure 4. Conceptual diagram of the Buffer Storage Humidity Model.

nvent di  M air,i . m inf,i (a i ) nvent .m v,k,i (v,k,i i )  .Wg,i dωi  Mair,i dt= minf,i(ωa − ωi) + ∑k mv,k,i(ωv,k,i − ωi) + Wg,i dt nlink k (6) nlink (6) . + ∑ mml,lc,c,i,i((ωll,,cc,,ii −ωii)  +βsursurf f((ωsurfsur f −ωi i)) cc

dωsur f Msur f κsur f f (ϕ, ω) dsurf= βsur f (ωi − ωsur f ) + βdeep(ωdeep − ωsur f ) (7) M  f (,) dt   (   )   (   ) (7) surf surf dt surf i surf deep deep surf dωdeep M κ f (ϕ, ω) = β (ω − ω ) (8) deep deep dt deep sur f deep ddeep M  f (,)   (  ) (8) deep deep dt deep surf deep Table 9. Properties of building materials for the Buffer Storage Humidity Model. Not only was the moisture adsorption‐desorption of the building materials considered, but also Gradient of Sorptive Isothermal that Buildingof the papers Materials in the offices. The amount of papers stored inside the offices was quoted from Density (kg/m3) Line ((kg (Water)/kg (Building Diffusion Resistance (–) actual surveyand Paper results [48] and set to 5.7 fm/person. The unit fm means the height (m: meter) of the Material))/(Relative Humidity)) cumulated A4 size (210 mm × 297 mm) papers. Because the maximum number of occupant in this Acoustic board 300 0.013 1 3 office buildingConcrete is 41 persons/floor, 2200 the total amount of papers 0.040 is 14.60 m /floor. The total 70 surface area of papersGypsum was board calculated assuming 910 that papers occupied 25% 0.015 of the desk surface area. These 8 papers were Cementmodeled mortar as one part of 2000 the walls in the simulations. 0.020 Table 9 shows the 35 moisture Polystyrene foam 20 0.700 50 adsorptionPaper‐desorption property 100of the building materials, 0.120 as well as one piece of paper. 53 These properties were set based on the Japanese database (materials) in WUFI pro 4.2. The values in database were estimated by Japan Testing Center for Construction Materials (JTCCM). Adsorption Using the wall area shown in Figure1, the thickness of each layer from Table1, the thermal properties in Table2 and the properties presented in Table9, the parameters of the Buffer Storage Humidity Model for a standard ﬂoor were estimated (Table 10). Energies 2016, 9, 875 13 of 25

Table 10. Parameters setup of the Buffer Storage Humidity Model for a standard ﬂoor.

Surface Buffer Storage Deep Buffer Storage Zone 1 2 3 1 2 3 βsurf κsurf Msurf βdeep κdeep Mdeep Ofﬁce 2444.2 0.016 2660.4 814.7 1 7326.7 Elevator hall/corridor 258.7 0.015 497.4 86.2 1 753.1 Staircase (east, west) 175.9 0.033 1239.3 58.6 1 551.6 Elevator shaft 113.8 0.015 344.2 37.9 1 151.0 Warehouse/service room 152.2 0.015 331.7 50.7 1 380.3 Toilets 258.7 0.015 497.4 86.2 1 753.1 Duct space/machine room 174.7 0.037 2755.1 58.2 1 305.2 1 2 The unit of βsurf and βdeep is kg (air)/h; the unit of κsurf and κdeep is (kg (water)/kg 3 (building material))/(relative humidity); the unit of Msurf and Mdeep is kg (building material)/h.

As shown in Table9, compared to the moisture diffusion resistance of air, that of building materials was 8–70-times greater; thus, the moisture adsorption-desorption occurred predominantly between the zone node and the surface storage. Furthermore, this study focused on condensation on wall surfaces, microbial viability due to condensation and the spreading of microbial contamination due to air movements; therefore, the estimation of condensation was targeted on only wall surfaces. In other words, concealed condensation was not considered.

2.1.6. Index of Condensation Risk TRNSYS judges condensation based on the magnitude correlation of the surface temperature and the dew-point temperature of air. If condensation occurred on a wall surface, the judgement was one, and if not, the judgement was zero. This was only one way to determine whether or not condensation occurred; for example, it evaluated the condensation occurring on large surface areas, like the office floor area (414.72 m2), and that on small surface areas, like the windows in the core parts (1.92 m2), equally. Therefore, it was necessary that condensation on wall surfaces be estimated in consideration of the area of the wall surface. In this study, the three indicators of the condensation ratio, condensation frequency and condensation risk, as given below, were defined and evaluated. By taking the area of a wall surface n (= 1, 2, ... , 452 surfaces) as An and the occurrence (judgement = 1) or non-occurrence (judgement = 0) of condensation on the wall surface n during time step t (=1, 2, ... , 8760 hours) as ICn,t, the condensation ratio CRt in time t was defined using Equation (9); the condensation frequency CFn for wall surface n was defined using Equation (10); and condensation risk CR throughout the year was defined using Equation (11).

452 ∑ ICn,t An n=1 CRt = × 100 (t = 1, 2, ..., 8760) (9) 452 ∑ An n=1 8760 ∑ ICn,t = CF = t 0 × 100 (n = 1, 2, ..., 452) (10) n 8760 452 ∑ CFn An = CR = n 1 (11) 452 ∑ An n=1

The CRt is an indicator that expresses the ratio of wall area where condensation has occurred to total wall area in the building and has one value for each time step. The CFn is an indicator that expresses the ratio of total hours when condensation has occurred to the 8760 h (one year) for wall Energies 2016, 9, 875 13 of 23

By taking the area of a wall surface n (= 1, 2, …, 452 surfaces) as An and the occurrence (judgement = 1) or non‐occurrence (judgement = 0) of condensation on the wall surface n during time step t (=1, 2, …, 8760 hours) as ICn,t, the condensation ratio CRt in time t was defined using Equation (9); the condensation frequency CFn for wall surface n was defined using Equation (10); and condensation risk CR throughout the year was defined using Equation (11).

452 ICn,t An n1 CRt  452 100 (t 1,2,...,8760) (9)  An n1 Energies 2016, 9, 875 14 of 25 8760  ICn,t surface n in the building and has 452t 0 values for each time step. The CR is an indicator calculated(10) from CFn  100 (n 1,2,...,452) the areal mean CFn of all wall surfaces8760 in the building and has one value for the entire building for the A 2 year. The summation of n, total area of 452 surfaces,452 is 10,980.3 m . CF A 2.2. Results and Discussion of Condensation Risk Estimation n undern Reference Conditions n1 CR  452 (11) Figure5 shows the CRt throughout the year. The maximum CRt occurred on December 6 at 7 a.m.,  An and the CR for the year was 0.353%. Most of the condensationn1 occurred in winter (December–March). Compared to the CRt in winter, although the value is very small, condensation also occurred in the intermediateThe CRt periodsis an indicator (April andthat October–November).expresses the ratio of wall area where condensation has occurred to total Figurewall area6 shows in the the buildingCR for each and floor.has one The value risk was for highesteach time for thestep. topmost The CF floor.n is an Because indicator the roofthat ofexpresses the top floorthe ratio is exposed of total to hours OA of when low temperature condensation in winter, has occurred the surface to the temperature 8760 h (one of year) the roof for tends wall tosurface decrease n in easily,the building which and can has induce 452 condensationvalues for each on time the step. wall The surfaces. CR is Therefore,an indicator it calculated was concluded from thatthe areal intensifying mean CF then of performance all wall surfaces of thermal in the insulation building and of the has roof one would value reduce for theCR entires effectively. building for the year. The summation of An, total area of 452 surfaces, is 10,980.3 m2. Figure7 shows the CRt of the day when it was at its maximum and before and after three days. Most of the condensation that occurred in the offices happened when the air-conditioning system2.2. Results was and not Discussion in operation, of Condensation and there was Risk minimal Estimation condensation under Reference when Conditions the air-conditioning system was running.Figure 5 Moreover,shows the evenCRt throughout when the air-conditioning the year. The maximum system was CR nott occurred in operation, on December condensation 6 at occurrence7 a.m., and was the markedly CR for lessthe as year compared was 0.353%. to the core Most parts. of Thus,the condensation the condensation occurred countermeasures in winter in(December–March). non-air-conditioned Compared core parts to arethe keyCRt pointsin winter, for thealthough restriction the value of condensation is very small, problems condensation in the entirealso occurred building. in the intermediate periods (April and October–November).

2 Condensation raito (%)

0 123456789101112 Month

Figure 5. Annual condensation ratio. Energies 2016, 9, 875 14 of 23 Figure 6 shows the CR for each floor. The risk was highest for the topmost floor. Because the roof of the top floor is exposed1.2 to OA of low temperature in winter, the surface temperature of the roof tends to decrease easily, which can induce condensation on the wall0.9874 surfaces. Therefore, it was concluded that intensifying0.9 the performance of thermal insulation of the roof would reduce CRs effectively.

0.6 0.4511 0.3430 0.3 0.1694 Condensation risk (%) risk Condensation 0.0740 0.0858 0 123456 Floor Figure 6. Condensation risk for each floor. Figure 6. Condensation risk for each ﬂoor.

Figure 7 shows the CRt of the day when it was at its maximum and before and after three days. Most of the condensation that occurred in the offices happened when the air‐conditioning system was not in operation, and there was minimal condensation when the air‐conditioning system was running. Moreover, even when the air‐conditioning system was not in operation, condensation occurrence was markedly less as compared to the core parts. Thus, the condensation countermeasures in non‐air‐conditioned core parts are key points for the restriction of condensation problems in the entire building.

AllEntire of the building building OfficeOffice only only 10 AC AC AC AC AC 8

2 Condensation ratio (%)

0 3/December 4/December 5/December 6/December 7/December 8/December 9/December (Thursday) (Friday) (Saturday) (Sunday) (Monday) (Tuesday) (Wednesday) Day/Month (Day of week) Figure 7. Condensation ratio in a week (December 3–December 9). AC = air‐conditioning on.

3. Condensation Risk Estimations under Varying Airtightness Conditions In this section, the influence of variations in the airtightness of windows on condensation and a method to restrain such condensation are discussed.

3.1. Case Setup for Airtightness Thermal insulation specifications of the external walls, roof and windows were fixed to the reference conditions mentioned in Section 2.1. In accordance with the airtightness grade stipulated in JIS A 4706 [41], the assessment of CR was conducted by changing the airtightness of the windows in the offices and core parts. Table 11 shows a summary of the airtightness grades according to JIS. The A‐4 grade indicates the highest performance, with Grades A‐3 A‐2, and A‐1 representing decreasing orders of airtightness performance.

Energies 2016, 9, 875 14 of 23

1.2 0.9874 0.9

0.6 0.4511 0.3430 0.3 0.1694 Condensation risk (%) risk Condensation 0.0740 0.0858 0 123456 Floor Figure 6. Condensation risk for each floor.

Figure 7 shows the CRt of the day when it was at its maximum and before and after three days. Most of the condensation that occurred in the offices happened when the air‐conditioning system was not in operation, and there was minimal condensation when the air‐conditioning system was running. Moreover, even when the air‐conditioning system was not in operation, condensation occurrence was markedly less as compared to the core parts. Thus, the condensation Energiescountermeasures2016, 9, 875 in non‐air‐conditioned core parts are key points for the restriction of condensation15 of 25 problems in the entire building.

AllEntire of the building building OfficeOffice only only 10 AC AC AC AC AC 8

2 Condensation ratio (%)

0 3/December 4/December 5/December 6/December 7/December 8/December 9/December (Thursday) (Friday) (Saturday) (Sunday) (Monday) (Tuesday) (Wednesday) Day/Month (Day of week)

Figure 7. Condensation ratio in a week (December 3–December 9).9). AC = air air-conditioning‐conditioning on.

3. Condensation Condensation Risk Risk Estimations Estimations under under Varying Varying Airtightness Airtightness Conditions Conditions In this section, the inﬂuenceinfluence of variations in the airtightness of windows on condensation and a method to restrain such condensation areare discussed.discussed.

3.1. Case Setup for Airtightness Thermal insulation specifications specifications of the external walls, roof and windows were fixedfixed to the reference conditions mentioned in Section 2.12.1.. In accordance with thethe airtightnessairtightness grade stipulatedstipulated in JIS A 4706 [[41],41], the assessment of CR was conducted by changing the airtightness of the windows in the officesoffices and core parts. Table 11 shows a summary of the airtightness grades according to to JIS. JIS. The A-4A‐4 grade grade indicates indicates the the highest highest performance, performance, with Gradeswith Grades A-3 A-2, A and‐3 A A-1‐2, representingand A‐1 representing decreasing ordersdecreasing of airtightness orders of airtightness performance. performance.

Table 11. Airtightness of windows based on the Japanese Industrial Standard (JIS).

Mass Flow Coefﬁcient Grade Criterion Airﬂow Exponent (−) (kg/(s·m)@1 Pa) A-1 Area where ventilation is required 0.001000 1 A-2 1 Soundproofed, 0.000250 1 A-3 General building thermally-insulated or 0.000067 1 A-4 dust-proofed building 0.000017 1 1 The grade of A-2 corresponds to the airtightness performance of the reference condition.

3.2. Results and Discussion of Condensation Risk Estimations for Airtightness Figure8 shows a scatter diagram with crack characteristic values of windows versus CR. The risks were lower for windows with lower airtightness grades. Figure9 shows the mass flow rate of infiltration into the sixth floor of the east staircase, where the greatest condensation occurred on the day when the CRt was at its maximum and before and after three days. Figure 10 shows the relative humidity in the same zone for the same days. It is clear from these figures that for lower airtightness grades, the amount of OA entering through the gaps of the window is greater, causing the relative humidity of the staircase to decrease. This effect results in reduced CRs for lower airtightness grades. Energies 2016, 9, 875 15 of 23 Energies 2016, 9, 875 15 of 23

Table 11. Airtightness of windows based on the Japanese Industrial Standard (JIS). Table 11. Airtightness of windows based on the Japanese Industrial Standard (JIS). Mass Flow Coefficient Grade Criterion Mass Flow Coefficient Airflow Exponent (−) Grade Criterion (kg/(s∙m)@1 Pa) Airflow Exponent (−) (kg/(s∙m)@1 Pa) A‐1 Area where ventilation is required 0.001000 1 A‐1 Area where ventilation is required 0.001000 1 A‐2 1 0.000250 1 A‐2 1 Soundproofed, thermally‐insulated 0.000250 1 A‐3 General building Soundproofed, thermally‐insulated 0.000067 1 A‐3 General building or dust‐proofed building 0.000067 1 A‐4 or dust‐proofed building 0.000017 1 A‐4 0.000017 1 1 The grade of A‐2 corresponds to the airtightness performance of the reference condition. 1 The grade of A‐2 corresponds to the airtightness performance of the reference condition. 3.2. Results and Discussion of Condensation Risk Estimations for Airtightness 3.2. Results and Discussion of Condensation Risk Estimations for Airtightness Figure 8 shows a scatter diagram with crack characteristic values of windows versus CR. The Figure 8 shows a scatter diagram with crack characteristic values of windows versus CR. The risks were lower for windows with lower airtightness grades. Figure 9 shows the mass flow rate of risks were lower for windows with lower airtightness grades. Figure 9 shows the mass flow rate of infiltration into the sixth floor of the east staircase, where the greatest condensation occurred on the infiltration into the sixth floor of the east staircase, where the greatest condensation occurred on the day when the CRt was at its maximum and before and after three days. Figure 10 shows the relative day when the CRt was at its maximum and before and after three days. Figure 10 shows the relative humidity in the same zone for the same days. It is clear from these figures that for lower airtightness humidity in the same zone for the same days. It is clear from these figures that for lower airtightness grades, the amount of OA entering through the gaps of the window is greater, causing the relative grades,Energies 2016 the, 9amount, 875 of OA entering through the gaps of the window is greater, causing the relative16 of 25 humidity of the staircase to decrease. This effect results in reduced CRs for lower airtightness grades. humidity of the staircase to decrease. This effect results in reduced CRs for lower airtightness grades. 0.6 0.6 0.5 0.4557 0.4557 0.4338 0.5 0.4338 0.4 A-4 0.3532 A-4 A-3 0.3532 0.4 A-3 0.3 A-2 0.2479 0.3 A-2 0.2479 0.2 A-1 0.2 A-1

Condensation risk (%) risk Condensation 0.1 Condensation risk (%) risk Condensation 0.1 0 0.000010 0.0001 0.001 0.01 0.00001 0.0001 0.001 0.01 Mass flow coefficient (kg/(s·m)@1Pa) Mass flow coefficient (kg/(s·m)@1Pa) Figure 8. Condensation risk under varying airtightness conditions. Figure 8. CondensationCondensation risk under varying airtightness conditions. 270 270 A-1 A-2 A-3 A-4 230 A-1 A-2 A-3 A-4 230 190 190

: Outflow 150 −

: Outflow 150 − 110 110 70

Mass flow rate (kg/h) rate flow Mass 70 + : + : Inflow, Mass flow rate (kg/h) rate flow Mass + : + : Inflow, 30 30 -10 -10 3/December 4/December 5/December 6/December 7/December 8/December 9/December 3/December(Thursday) 4/December(Friday) 5/December(Saturday) 6/December(Sunday) 7/December(Monday) 8/December(Tuesday) (Wednesday)9/December (Thursday) (Friday) (Saturday) (Sunday) (Monday) (Tuesday) (Wednesday) Day/Month Day/Month (Day of week) (Day of week) Figure 9. Mass flow rate of infiltration in the sixth floor of the east staircase (3 December–9 December). Figure 9. Mass flow rate of infiltration in the sixth floor of the east staircase (3 December–9 December). EnergiesFigure 2016, 9 9., 875Mass flow rate of infiltration in the sixth floor of the east staircase (3 December–9 December).16 of 23

100

Relative Humidity (%) Humidity Relative 20 A-1 A-2 A-3 A-4 0 3/December 4/December 5/December 6/December 7/December 8/December 9/December (Thursday) (Friday) (Saturday) (Sunday) (Monday) (Tuesday) (Wednesday) Day/Month (Day of week)

FigureFigure 10. 10. RelativeRelative humidity humidity in in the the sixth sixth floor ﬂoor of the east staircase (3 December–9 December).

Rather than follow the JIS standards for high airtightness that are effective at reducing air‐conditioning load and improving soundproofing and dust‐proofing, from the perspective of condensation reduction alone, CRs can be lowered with lower airtightness.

4. Condensation Risk Estimations under Varying Thermal Insulation Conditions In this section, condensation estimations by varying the thermal insulation performance of external walls, roof and windows and the specifications of the thermal insulation of these building parts to restrain condensation completely were discussed. After examining the insulation thickness of the external walls, by varying the thermal insulation performance of roof and glass, condensation estimations were conducted to investigate the thermal insulation conditions needed to realize non‐condensation in the building.

4.1. Condensation Risk Estimations for Thermal Insulation of External Walls

4.1.1. Case Setup for Thermal Insulation of External Walls Table 12 shows the case study settings. Using the roof specifications (thermal insulation thickness: 50 mm) and window specifications (single float glass) from the reference conditions, a case study was performed by altering only the thickness of the external walls’ thermal insulation (0–100 mm). Grade A‐2 was the standard for airtightness when analyzing the thermal insulation changes.

Table 12. Variation in the thickness of thermal insulation of the external wall.

External Wall 0 5 15 25 1 50 75 100 Thickness of Thermal Insulation (mm) The thickness of thermal insulation in Roof roof was fixed at 50 mm 2 Type of Glass The type of glass was fixed at single float glass 3 1, 2, 3 Reference conditions described in Section 2.1.

4.1.2. Results and Discussion of Condensation Risk Estimations for the Thermal Insulation of External Walls Figure 11 shows the correlation between the thickness of thermal insulation of the external walls and the CR. The risk decreased as the thickness of the thermal insulation of the external walls increased. However, above a thickness of 50 mm, there was no significant change in the CR with an increase in thickness of the thermal insulation.

Energies 2016, 9, 875 17 of 25

Rather than follow the JIS standards for high airtightness that are effective at reducing air-conditioning load and improving soundprooﬁng and dust-prooﬁng, from the perspective of condensation reduction alone, CRs can be lowered with lower airtightness.

4. Condensation Risk Estimations under Varying Thermal Insulation Conditions In this section, condensation estimations by varying the thermal insulation performance of external walls, roof and windows and the speciﬁcations of the thermal insulation of these building parts to restrain condensation completely were discussed. After examining the insulation thickness of the external walls, by varying the thermal insulation performance of roof and glass, condensation estimations were conducted to investigate the thermal insulation conditions needed to realize non-condensation in the building.

4.1. Condensation Risk Estimations for Thermal Insulation of External Walls

4.1.1. Case Setup for Thermal Insulation of External Walls Table 12 shows the case study settings. Using the roof specifications (thermal insulation thickness: 50 mm) and window specifications (single float glass) from the reference conditions, a case study was performed by altering only the thickness of the external walls’ thermal insulation (0–100 mm). Grade A-2 was the standard for airtightness when analyzing the thermal insulation changes.

Table 12. Variation in the thickness of thermal insulation of the external wall.

External Thickness of Thermal 0 5 15 25 1 50 75 100 Wall Insulation (mm) Roof The thickness of thermal insulation in roof was fixed at 50 mm 2 Type of Glass The type of glass was fixed at single float glass 3 1, 2, 3 Reference conditions described in Section 2.1.

4.1.2. Results and Discussion of Condensation Risk Estimations for the Thermal Insulation of External Walls Figure 11 shows the correlation between the thickness of thermal insulation of the external walls and the CR. The risk decreased as the thickness of the thermal insulation of the external walls increased. However, above a thickness of 50 mm, there was no signiﬁcant change in the CR with an increase in thicknessEnergies 2016 of, 9 the, 875 thermal insulation. 17 of 23

2.2146

2 1.4886

1 0.6662 0.3532

Ccondensation risk (%) 0.1650 0.1252 0.1108 0 0255075100 Thickness of thermal insulation (mm)

FigureFigure 11. Condensation risk with different thicknesses ofof insulationinsulation ofof thethe external wall (0–100 mm).

Condensation in all areas below the fifth floor, except for the windows, was suppressed completely when the thickness of the thermal insulation was 75 mm. However, for the sixth floor, condensation was present not only on the windows, but also on the external walls and roof. The results were similar for 100 mm‐thick thermal insulation. As mentioned in Section 2.2, improvement in thermal insulation of the roof is important for reducing CRs. Detailed analysis was conducted by increasing the thermal insulation thickness of the external walls from 50 mm–75 mm, 5 mm at a time, and observing the exact thickness at which condensation failed to occur on all areas of Floors 1–5, except for the windows. Figure 12 shows the results of this detailed analysis. There was no considerable change in the CR of the building as a whole. The results also indicated that condensation failed to occur with a thickness of 75 mm on all areas of Floors 1–5, except the windows.

0.2 0.1650 0.1522 0.1431 0.1358 0.1302 0.1252

0.1 Condensation risk (%) risk Condensation

0 50 55 60 65 70 75 Thickness of thermal insulation (mm) Figure 12. Condensation risk with different thicknesses of the insulation of the external wall (50–75 mm).

Increasing the thermal insulation thickness of the external walls to 75 mm completely suppressed condensation on all areas of Floors 1–5, except the windows, but condensation still occurred on the ceiling and external walls of the topmost floor. Even after increasing the thermal insulation material thickness of the external walls from 75 m–100 mm, condensation continued to occur on the topmost floor in places other than the windows. Furthermore, it caused no significant change in the CR of the building as a whole.

4.2. Condensation Risk Estimations for the Thermal Insulation of the Roof

4.2.1. Case Setup for the Thermal Insulation of the Roof As the second step for reinforcement of thermal insulation, the thickness at which condensation on all areas of the topmost floor other than the windows was suppressed was investigated, by

Energies 2016, 9, 875 17 of 23

2.2146

2 1.4886

1 0.6662 0.3532

Ccondensation risk (%) 0.1650 0.1252 0.1108 0 0255075100 Thickness of thermal insulation (mm) Energies 2016, 9, 875 18 of 25 Figure 11. Condensation risk with different thicknesses of insulation of the external wall (0–100 mm).

Condensation in in all all areas areas below below the fifththe floor,fifth exceptfloor, forexcept the windows,for the windows, was suppressed was suppressed completely whencompletely the thickness when the of thickness the thermal of insulationthe thermal was insulation 75 mm. However,was 75 mm. for However, the sixth floor, for the condensation sixth floor, wascondensation present not was only present on the not windows, only on but the also windows, on the external but also walls on andthe external roof. The walls results and were roof. similar The forresults 100 mm-thickwere similar thermal for 100 insulation. mm‐thick As thermal mentioned insulation. in Section As mentioned2.2, improvement in Section in thermal 2.2, improvement insulation ofin thethermal roof isinsulation important of for the reducing roof is importantCRs. for reducing CRs. Detailed analysis was conductedconducted by increasingincreasing thethe thermalthermal insulationinsulation thicknessthickness of thethe externalexternal wallswalls fromfrom 5050 mm–75mm–75 mm,mm, 55 mmmm atat aa time,time, andand observingobserving thethe exactexact thicknessthickness atat whichwhich condensationcondensation failedfailed toto occuroccur on allall areasareas ofof FloorsFloors 1–5,1–5, exceptexcept forfor thethe windows.windows. Figure 12 showsshows thethe resultsresults ofof thisthis detailed analysis.analysis. There was no considerable changechange inin thethe CRCR ofof thethe buildingbuilding asas aa whole.whole. The results also indicated that condensation failed to occur with a thickness of 75 mm on all areas of Floors 1–5, except thethe windows.windows.

0.2 0.1650 0.1522 0.1431 0.1358 0.1302 0.1252

0.1 Condensation risk (%) risk Condensation

0 50 55 60 65 70 75 Thickness of thermal insulation (mm)

Figure 12. 12. CondensationCondensation risk risk with with different different thicknesses thicknesses of the insulation of the insulation of the external of the wall external (50–75 mm). wall (50–75 mm). Increasing the thermal insulation thickness of the external walls to 75 mm completely suppressed condensation on all areas of Floors 1–5, except the windows, but condensation still Increasing the thermal insulation thickness of the external walls to 75 mm completely suppressed occurred on the ceiling and external walls of the topmost floor. Even after increasing the thermal condensation on all areas of Floors 1–5, except the windows, but condensation still occurred on the insulation material thickness of the external walls from 75 m–100 mm, condensation continued to ceiling and external walls of the topmost floor. Even after increasing the thermal insulation material occur on the topmost floor in places other than the windows. Furthermore, it caused no significant thickness of the external walls from 75 m–100 mm, condensation continued to occur on the topmost change in the CR of the building as a whole. floor in places other than the windows. Furthermore, it caused no significant change in the CR of the building as a whole. 4.2. Condensation Risk Estimations for the Thermal Insulation of the Roof 4.2. Condensation Risk Estimations for the Thermal Insulation of the Roof 4.2.1. Case Setup for the Thermal Insulation of the Roof 4.2.1.As Case the Setup second for step the for Thermal reinforcement Insulation of of thermal the Roof insulation, the thickness at which condensation on allAs areas the second of the step topmost for reinforcement floor other than of thermal the windows insulation, was the suppressed thickness at was which investigated, condensation by on all areas of the topmost floor other than the windows was suppressed was investigated, by keeping the thermal insulation thickness of the external walls at 75 mm and the type of glasses at single float glass and increasing the thermal insulation thickness of the roof from 50 mm upwards, 5 mm at a time.

4.2.2. Results and Discussion of Condensation Risk Estimations for Thermal Insulation of Roof As a result, condensation was suppressed completely on all areas of the topmost ﬂoor except the windows when the thermal insulation material thickness of the roof was 105 mm. The CR at this point was 0.109%. Figure 13 shows the CFn for the windows of each zone when the thermal insulation material thickness of the external walls was 75 mm and that of the rooftop was 105 mm. Although condensation on the external walls and roof was suppressed completely, there was still a large amount of condensation occurring on the windows, particularly in the core parts of Floors 4–6, where the Energies 2016, 9, 875 18 of 23

keeping the thermal insulation thickness of the external walls at 75 mm and the type of glasses at single float glass and increasing the thermal insulation thickness of the roof from 50 mm upwards, 5 mm at a time.

4.2.2. Results and Discussion of Condensation Risk Estimations for Thermal Insulation of Roof As a result, condensation was suppressed completely on all areas of the topmost floor except the windows when the thermal insulation material thickness of the roof was 105 mm. The CR at this point was 0.109%. Figure 13 shows the CFn for the windows of each zone when the thermal insulation material thickness of the external walls was 75 mm and that of the rooftop was 105 mm. Although Energies 2016, 9, 875 19 of 25 condensation on the external walls and roof was suppressed completely, there was still a large amount of condensation occurring on the windows, particularly in the core parts of Floors 4–6, where CFthen CFwasn was above above 10%, 10%, and and the eastthe east staircase staircase of the of topmost the topmost ﬂoor, floor, where where condensation condensation occurrence occurrence was greatest,was greatest, at above at above 20%. 20%.

25 20.7 20 18.0 16.8 15.9 14.6 14.2 14.7 15 13.9 13.1 11.3 11.3 10.4 10.2 10.4 10 8.5 8.4 8.6 7.1 7.2 7.6 7.2 6.2 5.3 5.1 5.2 4.2 5 3.2 3.7 3.3 2.4 1.8 2.4 0.4 0.3 0.7 0.6 0 Toilet Toilet Toilet Toilet Toilet Toilet Office Office Office Office Office Office Condensation frequency (%) Windbreak Staircase (East) Staircase (East) Staircase (East) Staircase (East) Staircase (East) Staircase (East) Staircase (West) Staircase (West) Staircase (West) Staircase (West) Staircase (West) Staircase (West) Elelvator hall/corridor Elelvator hall/corridor Elelvator hall/corridor Elelvator hall/corridor Elelvator hall/corridor Elelvator hall/corridor Warehouse/service room Warehouse/service room Warehouse/service room Warehouse/service room Warehouse/service room 1F 2F 3F 4F 5F 6F Figure 13. Condensation frequency for the windows in each zone (thermal insulation of external Figure 13. Condensation frequency for the windows in each zone (thermal insulation of external the the wall = 75 mm, thermal insulation of the roof = 105 mm). wall = 75 mm, thermal insulation of the roof = 105 mm). 4.3. Condensation Risk Estimations for Thermal Insulation of Glass 4.3. Condensation Risk Estimations for Thermal Insulation of Glass 4.3.1. Case Setup for Thermal Insulation of Glass 4.3.1. Case Setup for Thermal Insulation of Glass From the results in the Sections 4.1 and 4.2, it can be concluded that improving the thermal From the results in the Sections 4.1 and 4.2, it can be concluded that improving the thermal insulation of the windows was particularly important, making it essential to take countermeasures. insulation of the windows was particularly important, making it essential to take countermeasures. For this reason, the thermal insulation performance of glass was enhanced until condensation For this reason, the thermal insulation performance of glass was enhanced until condensation stopped stopped occurring on them. Thus, by intensifying the thermal insulation performance of windows as occurring on them. Thus, by intensifying the thermal insulation performance of windows as shown in shown in Table 13, condensation estimations were carried out. The thermal insulation thickness of Table 13, condensation estimations were carried out. The thermal insulation thickness of the external the external walls and the roof were fixed at 75 mm and 105 mm. walls and the roof were ﬁxed at 75 mm and 105 mm.

Table 13.13. Enhancement ofof thethe thermalthermal insulationinsulation performanceperformance ofof glass.glass. Solar Heat Gain Shading Type of Glass U‐Factor (W/(m2∙K)) Frame U-Factor Solar HeatCoefficient Gain (−) CoefficientShading (−) Type of Glass 2 Frame Single float 1 (W/(m ·K))5.53 Coefficient0.797 (−) Coefficient0.78 (−) Aluminum type; area ratio SingleDouble float 1 float 5.533.35 0.7970.782 0.780.91 ofAluminum frame to window type; = area 0.15; ratio of DoubleDouble float low‐e 3.352.53 0.7820.567 0.910.66 solarframe absorptance to window = 0.6; = 0.15; 2 DoubleTriple low-e float 2.532.00 0.5670.700 0.660.78 U‐factorsolar = 2.27 absorptance W/(m ∙K) = 0.6; Triple1 Single float float glass corresponds 2.00 to the 0.700thermal insulation performance 0.78 of theU-factor reference = 2.27 condition. W/(m2 ·K) 1 Single float glass corresponds to the thermal insulation performance of the reference condition.

4.3.2. Results and Discussion of Condensation Risk Estimations for Thermal Insulation of Glass Figure 14 shows a scatter diagram with the U-factor of the windows versus the CR. Although several values could be used as indicators of window performance, the U-factor was selected, as correlation with the CR is considered to be dependent mainly on the U-factor. As a result, even double low-e glass could not eliminate condensation. It was not until the adoption of the triple ﬂoat glass (U-factor = 2.0 W/(m2·K)) that condensation was completely suppressed in the entire building. Energies 2016, 9, 875 19 of 23

4.3.2. Results and Discussion of Condensation Risk Estimations for Thermal Insulation of Glass Figure 14 shows a scatter diagram with the U‐factor of the windows versus the CR. Although several values could be used as indicators of window performance, the U‐factor was selected, as correlation with the CR is considered to be dependent mainly on the U‐factor. As a result, even double low‐e glass could not eliminate condensation. It was not until the adoption of the triple float glass Energies 2016, 9, 875 20 of 25 (U‐factor = 2.0 W/(m2∙K)) that condensation was completely suppressed in the entire building.

0.20

0.15 Single float 0.1089 0.10 Double low-e 0.05 Triple float Double float

Condensation risk (%) risk Condensation 0.0063 0 0.0009 0 0123456 2 Heat transfer coefficient (U-factor) of window (W/(m ·K))

Figure 14. HeatHeat transfer transfer coefficients coefﬁcients (U (U-factors)‐factors) of windows windows and and condensation condensation risk (thermal (thermal insulation of external the wall = 75 mm, thermal insulation of the roof = 105 105 mm). mm).

It is not possible to control the generation of water vapor inside the office building, as the It is not possible to control the generation of water vapor inside the ofﬁce building, as the exhalation of the occupants is a source of water vapor. Therefore, regarding the factors for condensation exhalation of the occupants is a source of water vapor. Therefore, regarding the factors for condensation occurrence in winter, the only way to restrain condensation is by controlling the drop in wall surface occurrence in winter, the only way to restrain condensation is by controlling the drop in wall surface temperature, or in other words, by increasing the thermal insulation performance of the walls. temperature, or in other words, by increasing the thermal insulation performance of the walls.

5. Conclusions Conclusions In this study, a CR assessment of the entire office office building was conducted throughout throughout the the year, year, including when the air air-conditioning‐conditioning system was not in operation, by considering the heat transfer between zones, the absorption absorption-desorption‐desorption properties of the building materials and papers stored in the rooms and the air movements within the entire building. Furthermore, an analysis to identify the impact ofof variations variations in thein the thermal thermal insulation insulation of the of external the external walls, roof walls, and windowsroof and andwindows airtightness and airtightnessof windows of on windowsCRs was on performed, CRs was performed, with the aim with of controllingthe aim of controllingCRs. The results CRs. The of thisresults study of this are studyas follows: are as follows: 1. Most of the condensation occurred in winter (December–March) with minimal condensation 1 Most of the condensation occurred in winter (December–March) with minimal condensation occurring in the intermediate periods (April–May and October–November). occurring in the intermediate periods (April–May and October–November). 2. For the topmost floor, because the roof surface is in contact with the OA during winter, the 2 Forsurface the topmosttemperature floor, of because the roof the tends roof surface to decrease is in contact easily, withresulting the OA in duringcondensation. winter, theTherefore, surface temperatureimproving the of thermal the roof insulation tends to decrease of the roof easily, would resulting be effective in condensation. in reducing Therefore, CRs. improving 3. theThe thermal occurrence insulation of condensation of the roof was would significantly be effective less in in reducing air‐conditionedCRs. offices as compared to 3 Thenon‐ occurrenceair‐conditioned of condensation core parts. was Thus, significantly it can less be in air-conditionedconcluded that offices the ascondensation compared to non-air-conditionedcountermeasures in core non parts.‐air‐conditioned Thus, it can becore concluded parts are that important the condensation for the countermeasures restriction of incondensation non-air-conditioned within the core entire parts building. are important for the restriction of condensation within the 4. entireFrom the building. perspective of air‐conditioning load, soundproofing and dust‐proofing measures, the 4 Fromuse of the a highly perspective airtight of window air-conditioning was more load, helpful soundproofing than the JIS and standards. dust-proofing However, measures, from the useperspective of a highly of condensation airtight window reduction, was more when helpful the airtightness than the JISof a standards. window was However, of a lower from grade, the perspectivethe humidity of condensationratio of the rooms reduction, in winter when thedecreased airtightness due ofto a the window infiltration was of of a loweroutside grade, air thecontaining humidity less ratio water of the vapor rooms than in the winter inside decreased air, which due resulted to the infiltration in lowered of outsideCRs. air containing 5. lessUsing water thermal vapor insulation than the insidematerials air, which75 mm resulted thick on in the lowered externalCR s.walls completely suppressed 5 Usingcondensation thermal on insulation all areas materialsof Floors 1–5 75 mm except thick the on windows, the external but it walls still completelyoccurred on suppressed the ceiling condensation on all areas of Floors 1–5 except the windows, but it still occurred on the ceiling and external walls of the topmost floor. Even after increasing the thermal insulation material thickness of the external walls from 75 mm–100 mm, condensation continued to occur on the topmost floor on the windows, as well as other areas, necessitating an increase in the thickness of the thermal insulation materials of the roof. The thickness at which condensation was suppressed completely on all areas of the topmost floor except the windows was investigated, by keeping the Energies 2016, 9, 875 21 of 25

thermal insulation material thickness of the external walls at 75 mm and increasing the thickness of the materials of the roof from 50 mm upwards. By increasing the thickness up to 105 mm, condensation was suppressed completely throughout the building except for on the windows. However, a large amount of condensation occurred on the windows, making it necessary to improve their thermal insulation performance. Therefore, enhancement of thermal insulation is essential for suppressing condensation, especially of the roof and windows. 6 For the building in Tokyo that was the subject of this study, condensation within the building was suppressed completely when the thermal insulation material thickness of the external walls was greater than 75 mm, that of the roof was greater than 105 mm and the windows had triple ﬂoat glass (U-factor: 2.0 W/(m2·K)) or better.

Future studies may focus on the CR assessment based on variations in the orientation of the buildings and the location of core parts and whether the windows are open or closed. Furthermore, as the present study focused on only one area and one building, similar studies on buildings of different sizes or in areas with different weather conditions should be conducted. Investigations into the correlation between CR and air-conditioning load and condensation within air-conditioning units are also necessary.

Acknowledgments: The authors would like to thank Shouhei Teranishi of the Shin Nippon Air Technologies Co., LTD. He contributed to one part of the simulation setup and subsequent data analysis during a master’s course at Kanagawa University. Author Contributions: Wanghee Cho performed the simulations, analyzed the simulation results and wrote the paper. Shizuo Iwamoto designed the simulations. Shinsuke Kato reviewed the paper. All authors have read and approved the final manuscript. Conflicts of Interest: The authors declare no conflict of interest.

Abbreviation The following abbreviations are used in this manuscript: ◦ Tground Ground temperature, C ◦ Tmean Mean ground temperature (average air temperature), C Amplitude of surface temperature (maximum air temperature−minimum air T amp temperature), ◦C D Depth below surface, m α Thermal diffusivity of the ground (soil), m2/h tnow Current day of the year, 1, 2, . . . , 365 tshift Day of the year corresponding to the minimum surface temperature, 1, 2, ... , 365 3 VSA Airflow rate of supply air, m /h qSH Sensible-heat load of the office, kJ/h cA Specific heat of air, kJ/(kg·K) 3 ρA Density of air, kg/m ◦ ∆TOffice_SA Difference in temperature between the office and SA, C ◦ TERV Outlet temperature of the enthalpy recovery ventilator, C ◦ TOA Temperature of outdoor air, C Sensible-heat exchange efficiency of the enthalpy recovery ventilator, η SH dimensionless value ◦ TRA Temperature of return air, C XERV Humidity ratio of the enthalpy recovery ventilator, kg/kg dry air XOA Humidity ratio of outdoor air, kg/kg dry air Latent-heat exchange efficiency of the enthalpy recovery ventilator, η LH dimensionless value Energies 2016, 9, 875 22 of 25

XRA Humidity ratio of return air, kg/kg dry air XSP_Humid Humidity ratio of set-point for humidification, kg/kg dry air qLH Latent-heat load of the office, kJ/h L Latent-heat of vaporization (kJ/kg) Mair,i Mass of air in zone i, kg ωi Humidity ratio of zone i, kg/kg dry air t Elapsed time, h m˙ inf,i Mass flow rate of infiltration, kg/h ωa Ambient humidity ratio, kg/kg dry air m˙ v,k,I Mass flow rate of ventilation type k, kg/h ωv,k,i Humidity ratio of ventilation type k, kg/kg dry air W˙ g,i Internal moisture gains, kg/h m˙ l,c,i Mass flow rate of air link type c, kg/h ωl,c,i Humidity ratio of air link type c, kg/kg dry air βsurf Mass transfer coefficient of surface storage, kg (air)/h ωsurf Humidity ratio of surface storage, kg/kg dry air Msurf Mass of surface storage, kg Gradient of sorptive isothermal line of surface storage, (kg (water)/kg κ surf (building material))/(relative humidity) f(ϕ,ω) Conversion factor from relative humidity to humidity ratio βdeep Mass transfer coefficient of deep storage, kg (air)/h ωdeep Humidity ratio of deep storage, kg/kg dry air Mdeep Mass of deep storage, kg Gradient of sorptive isothermal line of deep storage, (kg (water)/kg κ deep (building material))/(relative humidity) CRt Condensation ratio during time-step t,% Occurrence or non-occurrence of condensation on wall surface n during time-step IC n,t t, one or zero 2 An Area of a wall surface n, m CFn Condensation frequency for wall surface n,% CR Condensation risk, %

References

1. Becker, R. Condensation and mould growth in dwellings—Parametric and ﬁeld study. Build. Environ. 1984, 19, 243–250. [CrossRef] 2. Lawton, M.D.; Dales, R.E.; White, J. The inﬂuence of house characteristics in a Canadian community on microbiological contamination. Indoor Air 1998, 8, 2–11. [CrossRef] 3. Small, B.M. Creating mold-free buildings: A key to avoiding health effects of indoor molds. Arch. Environ. Health Int. J. 2003, 58, 523–527. [CrossRef][PubMed] 4. Lengsfeld, K.; Krus, M. Microorganisms on Facades—Reasons, Consequences and Measures. Available online: http://www.kuleuven.be/bwf/projects/annex41/protected/data/FhG%20Oct%202004%20Paper% 20A41-T3-D-04-5.pdf (accessed on 18 January 2016). 5. Pasanen, P.; Pasanen, A.L.; Jantunen, M. Water condensation promotes fungal growth in ventilation ducts. Indoor Air 1993, 3, 106–112. [CrossRef] 6. Fisk, W.J.; Lei-Gomez, Q.; Mendell, M.J. Meta-analyses of the associations of respiratory health effects with dampness and mold in homes. Indoor Air 2007, 17, 284–296. [CrossRef][PubMed] 7. Meyer, H.W.; Würtz, H.; Valbjørn, O.; Sigsgaard, T.; Gyntelberg, F. Moulds and Health—An Epidemiological Study. In Proceedings of the 9th International Conference on Indoor Air Quality and Climate, Vol. III, Indoor Air 2002, The International Academy of Indoor Air Sciences, Monterey, CA, USA, 30 June–5 July 2002; pp. 394–397. Energies 2016, 9, 875 23 of 25

8. Bush, R.K.; Portnoy, J.M.; Saxon, A.; Terr, A.I.; Wood, R.A. The medical effects of mold exposure. J. Allergy Clin. Immun. 2006, 117, 326–333. [CrossRef][PubMed] 9. Burge, S.; Hedge, A.; Wilson, S.; Bass, J.H.; Robertson, A. Sick building syndrome: A study of 4373 office workers. Ann. Occup. Hyg. 1987, 31, 493–504. [CrossRef][PubMed] 10. Mendell, M.J.; Lei-Gomez, Q.; Mirer, A.G.; Seppänen, O.; Brunner, G. Risk factors in heating, ventilating, and air-conditioning systems for occupant symptoms in US office buildings: The US EPA BASE study. Indoor Air 2008, 18, 301–316. [CrossRef][PubMed] 11. Maus, R.; Goppelsröder, A.; Umhauer, H. Survival of bacterial and mold spores in air filter media. Atmos. Environ. 2001, 35, 105–113. [CrossRef] 12. Yanagi, U.; Ikeda, K. A study on the behavior and control of microbial contamination in an air conditioning system: Part 1—Growth environment and contamination status of microbes. J. Environ. Eng. (Trans. AIJ) 2005, 7, 49–56. (In Japanese) 13. Occupational Safety and Health Administration (OSHA). Preventing Mold-Related Problems in the Indoor EnergiesWorkplace. 2016, 9, 875 Washington, DC: U.S. Department of Labor, Occupational Safety and Health Administration; Report22 of 23 No.: 3304–04N; Occupational Safety and Health Administration (OSHA): Washington, DC, USA, 2006. 14. Saito, H.; Fukuda, K.; Sawachi, T. Integration Model of Hygrothermal Analysis with Decay Process for Durability Assessment of Building Envelopes. In Building Simulation ;; Tsinghua Press: Beijing, China, 2012; Volume 5,5, pp.pp. 315–324.315–324. 15. Andrade, C.; Sarr ı́a,, J.; Alonso, C. Relative humidity in the interiorinterior of concrete exposed to natural and artificialartificial weathering. Cem. Concr. Res. 1999,, 29,, 1249–1259. [CrossRef] 16. Vafai, K.; Sarkar, Sarkar, S. S. Condensation Condensation effects effects in in a afibrous fibrous insulation insulation slab. slab. J. HeatJ. Heat Transf. Transf. 19861986, 108,, 108667–675., 667–675. 17. [Janssens,CrossRef ]A.; Hens, H. Interstitial condensation due to air leakage: A sensitivity analysis. J. Therm. Envel. 17. Janssens,Build. Sci. A.;2003 Hens,, 27, 15–29. H. Interstitial condensation due to air leakage: A sensitivity analysis. J. Therm. Envel. 18. Build.Gutt, G.S. Sci. 2003Condensation, 27, 15–29. in [ CrossRefattics: Are] vapor barriers really the answer? Energy Build. 1979, 2, 251–258. 18.19. Gutt,Bludau, G.S. C.; Condensation Zirkelbach, D.; in Künzel, attics: H.M. Are vaporCondensation barriers problems really the in answer? cool roofs.Energy Interface Build. J. RCI1979 2009, 2, ,27 251–258., 11–16. 20. [Zillig,CrossRef W.;] Lenz, K.; Sedlbauer, K.; Krus, M. Condensation on Facades—Influence of Construction Type and 19. Bludau,Orientation. C.; Zirkelbach,In Proceedings D.; of Künzel, the 2nd H.M. International Condensation Conference problems on Building in cool roofs. Physics,Interface Leuven, J. RCIBelgium,2009, 14–27, 11–16.18 September 2003; pp. 437–444. 20.21. Zillig,Sato, N.M.N.; W.; Lenz, Shirakawa, K.; Sedlbauer, M.A.; K.; Krus,Loh, M.K.; CondensationJohn, V.M. Influence on Facades—Influence of Thermal Properties of Construction of Materials Type and in Orientation.Condensation In and Proceedings Microorganism of the 2nd Growth International on Building Conference Façades. on Building In Proceedings Physics, Leuven,of the 11DBMC Belgium, 14–18International September Conference 2003; pp. on 437–444. Durability of Building Materials and Components, Istanbul, Turkey 11–14 21. Sato,May 2008; N.M.N.; pp. 11–14. Shirakawa, M.A.; Loh, K.; John, V.M. Influence of Thermal Properties of Materials in 22. CondensationAelenei, D.; Henriques, and Microorganism F.M.A. Analysis Growth of on the Building condensation Façades. risk In on Proceedings exterior surface of the of 11DBMC building International envelopes. ConferenceEnergy Build. on 2008 Durability, 40, 1866–1871. of Building Materials and Components, Istanbul, Turkey, 11–14 May 2008; 23. pp.Hien, 11–14. W.N.; Liping, W.; Chandra, A.N.; Pandey, A.R.; Xiaolin, W. Effects of double glazed facade on energy 22. Aelenei,consumption, D.; Henriques, thermal comfort F.M.A. Analysisand condensation of the condensation for a typical risk office on exterior building surface in Singapore. of building Energy envelopes. Build. Energy2005, 37 Build., 563–572.2008 , 40, 1866–1871. [CrossRef] 23.24. Hien,Song, W.N.;S.Y.; Jo, Liping, J.H.; Yeo, W.; Chandra, M.S.; Kim, A.N.; Y.D.; Pandey, Song, A.R.;K.D. Xiaolin,Evaluation W. Effectsof inside of surface double glazedcondensation facade onin double energy consumption,glazing window thermal system comfort with insulation and condensation spacer: A forcase a study typical of office residential building complex. in Singapore. Build. Environ.Energy Build.2007, 200542, 940–950., 37, 563–572. [CrossRef] 24.25. Song,Hamdan, S.Y.; M.A. Jo, J.H.; Layered Yeo, wall M.S.; design Kim, Y.D.; to prevent Song, moisture K.D. Evaluation condensation of inside on its surface inside condensation surface. Energ. in Convers. double glazingManag. 2002 window, 43, system1821–1828. with insulation spacer: A case study of residential complex. Build. Environ. 2007, 42, 26. 940–950.Liu, J.; Aizawa, [CrossRef H.;] Yoshino, H. CFD prediction of surface condensation on walls and its experimental 25. Hamdan,validation. M.A. Build. Layered Environ. wall 2004 design, 39, 905–911. to prevent moisture condensation on its inside surface. Energ. Convers. Manag. 2002 43 27. Ogniewicz, Y.;, Tien,, 1821–1828. C.L. Analysis [CrossRef of condensation] in porous insulation. Int. J. Heat Mass Transf. 1981, 24, 26. Liu, J.; Aizawa, H.; Yoshino, H. CFD prediction of surface condensation on walls and its experimental 421–429. validation. Build. Environ. 2004, 39, 905–911. [CrossRef] 28. Ge, G.; Xiao, F.; Wang, S. Neural network based prediction method for preventing condensation in chilled 27. Ogniewicz, Y.; Tien, C.L. Analysis of condensation in porous insulation. Int. J. Heat Mass Transf. 1981, 24, ceiling systems. Energy Build. 2012, 45, 290–298. 421–429. [CrossRef] 29. Mumma, S.A. Chilled ceilings in parallel with dedicated outdoor air systems: Addressing the concerns of 28. Ge, G.; Xiao, F.; Wang, S. Neural network based prediction method for preventing condensation in chilled condensation, capacity, and cost. ASHRAE Trans. 2002, 108, 220. ceiling systems. Energy Build. 2012, 45, 290–298. [CrossRef] 30. Muneer, T.; Abodahab, N. Frequency of condensation occurrence on double‐glazing in the United 29. Mumma, S.A. Chilled ceilings in parallel with dedicated outdoor air systems: Addressing the concerns of Kingdom. Energy Convers. Manag. 1998, 39, 717–726. condensation, capacity, and cost. ASHRAE Trans. 2002, 108, 220. 31. Boyd, D.; Cooper, P.; Oreszczyn, T. Condensation risk prediction: Addition of a condensation model to BREDEM. Build. Serv. Eng. Res. Technol. 1988, 9, 117–125. 32. Becker, R. Effects of heating patterns on internal surface temperatures and risk of condensation. Build. Environ. 1993, 28, 333–345. 33. Mumovic, D.; Ridley, I.; Oreszczyn, T.; Davies, M. Condensation risk: comparison of steady‐state and transient methods. Build. Serv. Eng. Res. Technol. 2006, 27, 219–233. 34. Yuzawa, H.; Sugihara Y.; Kondo, T.; Hayashi, T.; Sekine, K.; Kohno, H.; Matsunawa, K.; Kato, S. Development of the Liquid Cooling Air‐Conditioning System for Commercial Buildings (Part 2) Modeling of the Building and Air‐Conditioning System for Feasibility Study. In Proceeding of the Society of Heating, Air‐Conditioning and Sanitary Engineers of Japan, Nagano, Japan, 25–27 September 2013; pp. 21–24. (In Japanese) 35. Method for Calculations and Judgements in Conformity to the 2013 Building Energy Standard of Japan, Part 1. Non‐Residential Buildings, 1st ed.; National Institute for Land and Infrastructure Management and Building Research Institute, Rengo printing center Co., Ltd.: Tokyo, Japan, 2013; pp. 118–128. (In Japanese) 36. Architectural Institute of Japan. Expanded AMeDAS Weather Data (1981–2000); Architectural Institute of Japan: Minato‐ku, Tokyo, Japan, 2005.

Energies 2016, 9, 875 24 of 25

30. Muneer, T.; Abodahab, N. Frequency of condensation occurrence on double-glazing in the United Kingdom. Energy Convers. Manag. 1998, 39, 717–726. [CrossRef] 31. Boyd, D.; Cooper, P.; Oreszczyn, T. Condensation risk prediction: Addition of a condensation model to BREDEM. Build. Serv. Eng. Res. Technol. 1988, 9, 117–125. [CrossRef] 32. Becker, R. Effects of heating patterns on internal surface temperatures and risk of condensation. Build. Environ. 1993, 28, 333–345. [CrossRef] 33. Mumovic, D.; Ridley, I.; Oreszczyn, T.; Davies, M. Condensation risk: comparison of steady-state and transient methods. Build. Serv. Eng. Res. Technol. 2006, 27, 219–233. [CrossRef] 34. Yuzawa, H.; Sugihara, Y.; Kondo, T.; Hayashi, T.; Sekine, K.; Kohno, H.; Matsunawa, K.; Kato, S. Development of the Liquid Cooling Air-Conditioning System for Commercial Buildings (Part 2) Modeling of the Building and Air-Conditioning System for Feasibility Study. In Proceedings of the Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, Nagano, Japan, 25–27 September 2013; pp. 21–24. (In Japanese) 35. Method for Calculations and Judgements in Conformity to the 2013 Building Energy Standard of Japan, Part 1. In Non-Residential Buildings, 1st ed.; National Institute for Land and Infrastructure Management and Building Research Institute, Rengo printing center Co., Ltd.: Tokyo, Japan, 2013; pp. 118–128. (In Japanese) 36. Architectural Institute of Japan. Expanded AMeDAS Weather Data (1981–2000); Architectural Institute of Japan: Minato-ku, Tokyo, Japan, 2005. 37. Kusuda, T.; Achenbach, P.R. Earth Temperature and Thermal Diffusivity at Selected Stations in the United States (No. NBS-8972); National Bureau of Standards Gaithersburg: Gaithersburg, MD, USA, 1965. 38. Thermal Energy System Specialist (TESS) Library Documentation. The Ground Source Heat Pump Component Library, Type501 GROUND TEMPERATURE PROFILE; Thermal Energy System Specialist (TESS): Madison, WI, USA, 2004. 39. Bureau of Construction, Tokyo Metropolitan Government, Ground of Tokyo (GIS version). Available online: http://www.kensetsu.metro.tokyo.jp/jigyo/tech/start/03-jyouhou/geo-web/00-index.html (accessed on 20 December 2015). 40. The Society of Heating, Air-Conditioning and Sanitary Engineers of Japan. The handbook of the Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, Vol.1 Fundamental, 14th ed.; The Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, Maruzen publishing Co., Ltd.: Tokyo, Japan, 2010; p. 414. (In Japanese) 41. Japanese Standards Association. Japanese Industrial Standard Committee, JIS A 4706 Windows; Japanese standards Association: Mita, Minato-ku, Tokyo, Japan, 2000. 42. Solar Energy Laboratory, Univ. of Wisconsin-Madison; TRANSSOLAR Energietechnik GmbH; CSTB—Centre Scientiﬁque et Technique de Bâtiment; TESS—Thermal Energy System Specialists, LLC. TRNFLOW Manual: TRNFLOW A Module of an Air Flow Network for Coupled Simulation with TYPE 56 (Multi Zone Building of TRNSYS); Solar Energy Laboratory, Univ. of Wisconsin-Madison: Madison, WI, USA, 2006. 43. Solar Energy Laboratory, Univ. of Wisconsin-Madison; TRANSSOLAR Energietechnik GmbH; CSTB—Centre Scientiﬁque et Technique de Bâtiment; TESS—Thermal Energy System Specialists, LLC. TRNSYS Manual: Volume 6 Multizone Building Modeling with Type56 and TRNBuild; Solar Energy Laboratory, Univ. of Wisconsin-Madison: Madison, WI, USA, 2007; pp. 142–150. 44. Woods, J.; Winkler, J.; Christensen, D. Evaluation of the Effective Moisture Penetration Depth Model for Estimating Moisture Buffering in Buildings, Technical Report of National Renewable Energy Lab. (NREL), 2013. Available online: http://www.osti.gov/scitech/biblio/1219896-evaluation-effective-moisture- penetration-depth-model-estimating-moisture-buffering-buildings (accessed on 21 January 2016). 45. Yoshino, H.; Mitamura, T.; Hasegawa, K. Moisture buffering and effect of ventilation rate and volume rate of hygrothermal materials in a single room under steady state exterior conditions. Build. Environ. 2009, 44, 1418–1425. [CrossRef] 46. Catalina, T.; Woloszyn, M.; Virgone, J. Impact of Moisture Buffering on Energy Performance of Cooling Ceilings. In Proceedings of the Annex 41 International Conference, Lyon, France, 25–27 October 2006. 47. Abadie, M.; Deblois, J.P.; Mendes, N. A Comparison Exercise for Calculating Heat and Moisture Transfers Using TRNSYS and PowerDomus. Available online: http://www.kuleuven.be/bwf/projects/annex41/ protected/data/PUCPR%20Oct%202005%20Paper%20A41-T1-Br-05-2.pdf (accessed on 6 January 2016). Energies 2016, 9, 875 25 of 25

48. Japan Image and Information Management Association (JIIMA), Suggested the Policy of Promoting Green Ofﬁce to the Minister of Public Management. Available online: http://www.jiima.or.jp/pdf/policy_ recommendations1.pdf (accessed on 12 December 2015). 49. Japanese Standards Association. Japanese Industrial Standard Committee, JIS A 1475 Method of Test for Hygroscopic Sorption Properties of Building Materials; Japanese Standards Association: Mita, Minato-ku, Tokyo, Japan, 2004.

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