Thermal comfort evaluation in cruise terminals

Accepted Manuscript Thermal comfort evaluation in cruise terminals Vitor Cardoso, Nuno M.M. Ramos, Ricardo M.S.F. Almeida, Eva Barreira, João Poças Martins, M. Lurdes Simões, Luís Sanhudo, Bruno Ribeiro PII:

S0360-1323(17)30457-2

DOI:

10.1016/j.buildenv.2017.10.008

Reference:

BAE 5121

To appear in:

Building and Environment

Received Date: 7 August 2017 Revised Date:

20 September 2017

Accepted Date: 4 October 2017

Please cite this article as: Cardoso V, Ramos NMM, Almeida RMSF, Barreira E, Martins JoãPoç, Lurdes Simões M, Sanhudo Luí, Ribeiro B, Thermal comfort evaluation in cruise terminals, Building and Environment (2017), doi: 10.1016/j.buildenv.2017.10.008. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Thermal comfort evaluation in cruise terminals Vitor Cardoso (1), Nuno M. M. Ramos (1), Ricardo M. S. F. Almeida (1),(2)*, Eva Barreira (1),

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João Poças Martins (1), M. Lurdes Simões (1), Luís Sanhudo (1), Bruno Ribeiro (1) (1)

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CONSTRUCT-LFC, Faculdade de Engenharia (FEUP), Universidade do Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal. (2) CI&DETS - Polytechnic Institute of Viseu, School of Technology and Management, Department of Civil Engineering, Campus Politécnico de Repeses, 3504-510 Viseu, Portugal. *

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Corresponding author: E-mail: [email protected], Tel: 00351 232480589, Fax: 00351 232424651

ABSTRACT

The variations of building typologies contribute to the difficulty of performing a correct analysis of the comfort conditions in buildings that do not fit the more common geometries

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and occupation patterns. The main objective of the article is to evaluate the comfort conditions of cruise terminal buildings, an example of this type of problem. A twofold strategy, comprising in-situ measurements and user surveys was implemented. A total of 20

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independent field measurements of thermal comfort parameters underwent in 2 facilities located in Portugal. The in-situ measurements supported the comfort assessment by the PMV

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analytical index and by the ASHRAE 55 and EN15251 adaptive approaches. The responses to 572 questionnaires to judge sensations and preferences of the passengers were obtained. Other aspects were also inquired, such as the time spent in the facilities and the health status. The comparison of the comfort assessment with the results of the survey showed that the adaptive models provided a broader acceptance of the measured environmental conditions, in line with the broader acceptance demonstrated by the users. The significant restriction of the PMV model application in this building typology was emphasized. The contrast of sensations by passengers of different national origin, with tropical originals feeling neutral at higher

ACCEPTED MANUSCRIPT operative temperatures than temperate climate originals, was detected as an influencing factor. Waiting time was another relevant factor found, as the time spent inside the buildings pointed to a greater demand by passengers.

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Keywords: Cruise terminal, Thermal comfort, PMV-PPD model, Adaptive models, Passengers, Questionnaire

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1. INTRODUCTION

Environmental sustainability and green energy sources are an ever more increasing

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concern in nowadays society. Policies to tackle the issues on energy consumption and carbon footprint in pivot domains, like the building sector, are a present reality in the European Union. By 2014, in the EU-28, the share of the building sector in final energy consumption was of approximately 40%. The CO2 emissions by this sector contributed with 36% of the

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total [1, 2]. The Energy Performance of Buildings Directive (EPBD) 2002/91/EC [3], and its recast [4], express the continuous orientation towards the preservation and reasonable use of energy in buildings [5].. Additionally, the increasing consideration on occupant performance,

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health and overall comfort, has to be addressed [6]. Building standards must pursue a weighted approach on the energy consumption and thermal comfort of users, since good

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indoor climate and environmental sustainability are strongly dependent on this symbiosis. The definition of what constitutes a comfortable environment depends on the thermal perception of the occupants. It is therefore a complex subject that can be influenced by past thermal history, non-thermal factors and thermal expectations [7]. The variations of building typologies contribute to the difficulty of performing a correct analysis of the comfort conditions in buildings that do not fit the more common geometries and occupation patterns. Cruise terminal buildings are a good example of this problem. Their geometry will frequently

ACCEPTED MANUSCRIPT correspond to a large volume space and the occupancy patterns are very different from wellstudied office spaces [8, 9], schools [10, 11] or commercial facilities [12]. Moreover, the effect of the air-conditioning system and the temperature/wind distribution are crucial for the indoor thermal comfort [13]. The expectations of the users, however, should be investigated

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in order to adequately design this specific type of buildings. The mobility of the passengers and the side effects of the environment inside the ship also play an important role [14, 15]. The research presented by Zheng et al. [16] proved the importance of ventilation and HVAC

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on the reduction of infectious disease propagation in cruise ships. These conclusions can be extended to cruise terminals, putting a focus on the necessity to achieve comfort conditions

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without compromising the health of the users.

Standardized methodologies for the evaluation of indoor thermal comfort include the PMV-PPD model described in ISO 7730 [17] and ASHRAE 55 [18], first developed by Fanger [19, 20]. Environmental factors (air temperature, humidity, air velocity and mean

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radiant temperature) and individual factors (activity and clothing insulation) make the basis on the heat balance of the human body in this model. The thermal comfort can also be analyzed with adaptive models [21, 22], which, according to EN 15251 [23] and ASHRAE 55

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[18], are valid for buildings without mechanical cooling systems where there is easy access to operable windows and occupants may freely adapt their clothing to the indoor and/or outdoor

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thermal conditions.

The perception of the thermal environment by the occupants, however, can diverge from the results defined by the standardized methodologies. This is likely to occur when the buildings do not fit the scope of the standards. Several thermal comfort studies brought this subject to light by conducting occupant surveys. Results in mechanically ventilated, mixedmode and free running buildings, show that surveyed subjects find comfort in a wider spectrum of conditions, leading to wider acceptable operative temperatures [24, 25]. This was

ACCEPTED MANUSCRIPT found for different types of climates according to Kottek et al. [26], except for type E – polar climates - environments and free running buildings were the predominant typology. A field work in several Portuguese cities, targeting office spaces, dwellings, elderly and educational buildings, found discrepancies with the standardized acceptability limits. It proved that the

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occupants can feel comfortable in a much broader range of temperatures, depending on local climate and building characteristics [27]. Physics and physiology alone do not express the thermal sensation of users accurately, even with little behavioral adaptation incorporated

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(clothing and air velocity adjustments). Several subjective factors (behavioral, physiological and psychological), influenced by climate, nature of buildings, thermal expectation, time

users in a given environment [28].

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spent indoors, social and cultural context, among others, take place in the thermal comfort of

The type C climatic regions – moist subtropical mid-latitude climates –, according to the Köppen-Geiger climate classification [26], are the ones with the wider thermal comfort range

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of temperatures observed during experimental studies [24]. Thus, the premise of low energy use has the most potential in them. For these reasons, it is important that studies from similar climatic zones, and preferably with a high cultural background overlap, should be the ones

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focused on a preliminary analysis. Considering that the field study presented in this study was conducted in this region, other examples from literature were therefore focused in similar

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climates.

Several proposals for the adaptation of standardized models can often be found in literature. A study for both winter and summer conditions was conducted in different university buildings of Bari, southern Italy [29]. It included thermal comfort surveys, with a total of 1849 polled subjects. A trend to overestimate the neutral temperatures by the PMV index was found.

ACCEPTED MANUSCRIPT Measurements in naturally ventilated university and high school classrooms in Turin, Italy, were conducted during morning and afternoon lessons. They showed an extension from the (-0.5; +0.5) to a (-0.5; +1.1) PMV vote acceptable intervals for category B buildings, emphasizing the acceptability of less homogeneous thermal environments. The slightly warm

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voted environments aligned with a prevailing no change choice by the users answers [30]. The same sort of conclusions were manifested in a more recent study [31].

Measurements in Portuguese free-running educational buildings were conducted during

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occupation periods, applying 1 min logging intervals of physical parameters and simultaneous questionnaires to occupants. 487 questionnaires were filled in this field work. It was

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concluded that acceptable environments align with the comfort ranges of adaptive models, while most of the monitored spaces failed to perform when classified by the PMV-PPD model [32]. Overall, the model predicted a lower mean thermal sensation than the one found in the surveys responses. Even so, the preference for slightly warmer environments was found since

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the mean thermal sensation (MTS = 1) goes along with a neutral mean thermal preference. Measured local thermal discomfort due to warm or cool floor met the category C requirements, while discomfort by radiant asymmetry fulfilled category A conditions,

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according to ISO 7730 [33]. Other studies on thermal comfort in educational buildings in Portugal align with the pointed conclusions [34, 35].

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A thermal evaluation in free running office buildings took place in Lyon, France, during August and September 2004 and March and June 2005 [36]. The data was collected in alternate visits during morning and afternoon for entire workweeks. The measuring device circulated among every workers desk for a 10 min measurement period, while the worker questionnaire filling underwent. The overestimation of the warm sensation in the warm season and the cool sensation in the cooling season by ISO 7730 [33] was pointed, underlining the inadequacy of this standard in the simulation of the thermal environment. The

ACCEPTED MANUSCRIPT sample answers got better comfort acceptability with ASHRAE 55 than with EN 15251, since the upper limits of the latter are slightly more conservative. In 2011, a study in northern Italy cities, during summer and winter seasons, was conducted with 575 independent thermal comfort surveys taking place amongst nine open

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plan offices. A low correlation between the mean thermal sensation of the workers and the PMV of the logged data was found [37]. It was emphasized that the lack of possibilities for the thermal environmental modification by the occupants and the low air speeds, which lead

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to dissatisfaction due to vertical air temperature gradient, were the probable causes.

During summer and winter months of 2012 and 2013 in airport terminals of London and

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Manchester, United Kingdom, a thermal comfort fieldwork was carried out, with simultaneous measurements and surveys to passengers and workers in the buildings [35]. The neutral preferred temperatures of the passengers were found to be lower than the measured indoor temperatures. This has implications in energy savings, by avoiding overheating in the

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winter.

Other authors also applied the PMV-PPD model to evaluate transport facilities. Katavoutas et al. [38] performed extensive measurements that allowed for an evaluation of the

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thermal comfort conditions on subway waiting platforms. The importance of design characteristics of the stations has been demonstrated as they lead to different interactions with

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the outdoor conditions.

The need for further study in different types of buildings is supported by the continuous improvement of standardized thermal comfort models. Several studies come up with their own adaptive comfort equations [39-41], besides the ones based in meta studies [21, 22]. The systematic comparison between the standardized models and the results from occupant surveys proved to be a solid strategy for a supported extension of the application scope of those models.

ACCEPTED MANUSCRIPT The objective of this work is to evaluate the comfort conditions of cruise terminal buildings. To do so, an extensive measurement campaign was performed and the collected data was analyzed in the frame of standardized thermal comfort models. An extensive survey to the comfort conditions acceptability of the users was performed. It is intended to:

model and the adaptive models; - Compare that evaluation with the results of the user surveys;

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- Evaluate the thermal comfort of two cruise terminal buildings using the PMV-PPD

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- Conclude on the applicability of the standardized models and detect possible causes for

2. METHODOLOGY 2.1 Case studies

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deviation between the models and the perception of the users.

The study took place in 2 cruise terminal buildings (BI and BII), located in the region of

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Porto, Portugal. The buildings are positioned at approximately 900 meters from each other. The building BI has a complex curve shape and it is composed by 3 floors above ground level and 1 below. There is a considerable opening in its central axis connecting all the floors above

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ground level. The envelope is a conciliation of self-compacted concrete with ceramic coating and big glazed surface areas. The building BII has a polygonal configuration with a 7-meter

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height gable roof on the ground floor. The building envelope is composed by a wood plated covering on a timber frame structure and limited glazed panels. The two buildings have a large floor area (1900 m2 in building BI and 800 m2 in building BII) and, therefore, a previous inspection to select the measurement points was required. The selection criterion was the occupancy rate and, therefore, the study was conducted in the areas of the buildings with higher concentration of cruise passengers during arrivals and departures. Thus, in building BI the main waiting zone located on the 1st floor was selected and in

ACCEPTED MANUSCRIPT building BII the waiting room occupies the majority of the indoor space. An exterior view of the buildings is presented in Table 1, which also introduces the most relevant geometric features of the buildings and shows the locations where the measurements took place. Measurements of global thermal comfort variables and of local thermal discomfort

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variables were carried out in each area with logging intervals of 30 s. Tourists and crew members standing or sitting in the previously referred areas were surveyed simultaneously with the measurements as seen in previous thermal comfort studies [30, 32]. The fieldwork

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went from April to May 2017.

The spring season aligns with an increase in cruise traffic, providing a greater number of

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passengers. A total of 10 cruises were targeted in this work, with an average of 57.2 respondents per arrival/departure, totaling 572 filled questionnaires. The sample average age ranged from 28 to 70 years old. The large size of the sample combined with the highly heterogeneous national origin provided robust material for a reliable analysis. Table 2 shows

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the scheduled times of the measurements, alongside the sample sizes. The region of Porto has a mild climate with dry summers. The number of degree-days of the heating period is 1250 (base 18˚C). Climatic data on exterior air temperature and relative

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humidity was acquired by a weather station located in the nearby area.

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Table 1. Buildings and surveyed spaces. BI

BII

Indoor

Floor area (m2)

1900

3

9320

800

6400

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Volume (m )

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Outdoor

Table 2. Fieldwork schedule and sample size. ID

BI

01 02 05 06 08 03 04 07 09 10

2.2 Equipment

Departure Start (h:m) Surveys (N) 13:00 67 13:17 73 13:26 56 13:23 34 13:21 49 14:54 15 13:18 21 17:06 17 12:48 20 13:43 18

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BII

Arrival Start (h:m) Surveys (N) 09:05 22 08:16 29 08:45 21 08:33 10 10:15 19 11:53 18 08:24 26 13:09 22 09:35 22 09:06 13

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Building

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The equipment used in the field campaign follows the ISO 7726 [42] guidelines. A set of probes described in Table 3, connected to a data logger, collected information regarding both global and local thermal comfort characterization variables. Relevant global comfort parameters included: air temperature, mean radiant temperature, air velocity and relative humidity at 1.10 m. The local thermal discomfort variables included: air temperature at head, abdomen ankle and floor levels and radiant asymmetry temperature. Exterior air temperature and relative humidity were recorded throughout the whole fieldwork duration.

ACCEPTED MANUSCRIPT Table 3. Technical specifications of the equipment. Probe height

Range

Resolution

Accuracy

1.10 m

-30 to +100°C

0.01°C

-0.09 to +0.19°C

Relative humidity [RH]

1.10 m

5% to 98%

0.10%

±2.5%

Air velocity [vair]

1.10 m

0.05 to 5 m/s

0.01 m/s

±0.02 m/s (0.05 m/s – 1 m/s) ±0.1 m/s (1 m/s – 5 m/s)

Mean radiant temperature [Trad]

1.10 m

-30 to +120°C

0.01°C

-0.09 to +0.21°C

Radiant asymmetry temperature [Trad.asymmetry]

1.10 m

-10 to +100°C

0.01°C

10.43 µV/(W/m²)

0.00 m

-10 to +100°C

0.01°C

-0.08 to +0.19°C

0.10 m

-10 to +100°C

0.01°C

-0.08 to +0.19°C

1.70 m

-10 to +100°C

0.01°C

-0.08 to +0.19°C

0.60 m

-10 to +100°C

0.01°C

-0.08 to +0.19°C

Air temperature [Ta]

(1)

Floor temperature [Tf]

(1)

Temperature at ankle level [Tk](1) Temperature at head level [Th]

(1)

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Temperature at abdomen level [Tb]

Both sitting and standing heights were covered with the positions chosen according to ISO 7726

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(1)

(1)

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Parameter

2.3 Questionnaire

Occupants were asked to fill an objective individual questionnaire to assess their perception of the thermal environment. The questionnaire is divided into 3 main parts: the first part regards personal information such as age, gender, weight, height and national origin,

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this last information is important for grouping the sampling according to climate and cultural background; the second part focus on the thermal perception, including 4 questions in consonance with the subjective scales presented in ISO 10551 [43] to assess thermal sensation

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(MTS), thermal preference (MTP), personal acceptability or thermal stress assessment (TSA)

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and personal tolerance (TOL); and the third part is dedicated to clothing insulation, in accordance with ASHRAE 55 [44] and ISO 7730 [33], using a simplified methodology based on 4 pre-established common clothing ensembles, which correspond to an insulation of 0.3, 0.5, 0.7 and 1.0 clo. In addition to these parts, 4 other questions were also included: a 3-scale question regarding current health perception (HS), which can be related to the sensibility and tolerability to wider temperature ranges; a 3-scale question regarding physical activity frequency (PA), which can be related to possible variations of the metabolic rate; the number of people traveling with the respondent, which can be related to a psychological effect [45];

ACCEPTED MANUSCRIPT and the time spent in the building (WT), which can be related to environmental personal adaptation [46]. In the entire experimental campaign, the metabolic rate was assumed as 1.2 met, in accordance with ISO 7730 [33] and ASHRAE 55 [44] for sedentary activity and

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standing (relaxed).

3. QUESTIONNAIRE RESULTS

In building BI, a total of 380 individual surveys were filled, of which 192 were males and

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188 females. In building BII, 192 passengers were enquired, of which 106 were males and 86 females. The box-plot representation of age and physical characteristics (weight and height)

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of the sample are shown in Figure 1, separately for each building. Although some differences can be pointed, the two datasets are quite homogeneous. In average, the sample is slightly older in building BII (49.1 in building BI and 51.1 in building BII), but, on the other hand, present a wider distribution in building BI. The weight distribution is quite similar in both

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samples (average weight of 68.0 kg in building BI and 68.5 kg in building BII) and the passengers are somewhat taller in building BII (in average) but present a narrower

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distribution.

(a)

(b)

(c)

Figure 1. Characterization of the sample: (a) age; (b) weight; (c) height.

ACCEPTED MANUSCRIPT As previously explained the clothing insulation was estimated assuming 4 pre-established clothing ensembles corresponding to 0.3, 0.5, 0.7 and 1.0 clo. A descriptive statistic of the results is presented in Table 4. No large differences between the two datasets can be pointed out. A trend for higher clothing insulation in the arrival is observed in both buildings, with an

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average of 0.64 clo and 0.65 clo in BI and BII, respectively. In the departure, these values decrease up to 0.50 clo and 0.58 clo.

BI

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Table 4. Clothing insulation descriptive statistics.

BII

Arrival

Departure

ID

01

0.49

0.49

03

02

0.61

0.50

05

0.79

0.51

06

0.89

0.63

08

0.4

0.35

Mean

0.64

0.50

Std. Dev.

0.18

0.09

C.V. [%]

29.0

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Arrival

Departure

0.48

0.54

04

0.72

0.66

07

0.54

0.37

09

0.80

0.78

10

0.72

0.56

Mean

0.65

0.58

Std. Dev.

0.12

0.14

C.V. [%]

19.0

23.0

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ID

The responses concerning the individual thermal sensation are presented in Figure 2 by

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gender. The idea behind this analysis is to provide an overall insight about the buildings

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thermal comfort according to its users. However, one should stress that the temperature at which each vote was made was not taken into account. The effect of gender did not prove very important as no large differences were found among the sets. In building BI, 35.8% of the respondents classified the thermal environment as neutral (its = 0), 29.2% as slightly warm or slightly cool (its = ±1) and 35.0% felt uncomfortable with the indoor environment (its = ±2 and ±3). In building BII, the majority of the respondents voted for an individual thermal sensation of neutral (52.6%), 30.2% classified the thermal environment as slightly

ACCEPTED MANUSCRIPT warm or slightly cool (its = ±1) and 17,2% considered it warm/hot or cool/cold (its = ±2 and

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±3).

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a) b) Figure 2. Individual thermal sensation by gender: a) building BI; b) building BII.

In both buildings, the mean thermal sensation, MTS, was near neutral: MTS = 0.37 and 0.25, in BI and in BII, respectively. The thermal preference was in accordance with these

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results as most of the occupants preferred maintaining the thermal environment unchanged (65.3% and 63.0% in BI and in BII, respectively). The mean thermal preference, MTP, was 0.11 in building BI and 0.03 in BII. Figure 3 presents the results of the individual thermal

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females.

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preference by gender. Once again, no large differences were found between males and

a) b) Figure 3. Individual thermal preference by gender: a) building BI; b) building BII.

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The importance of previous experiences in the evaluation of thermal comfort is well accepted. Thus, the national origin of the respondents can be a relevant parameter for their thermal sensation. For that purpose, the Koppen-Geigger climate classification was used for

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clustering the sample. Four groups were considered: (A) tropical; (B) arid; (C) temperate; and (D) continental. The large majority of the respondents came from temperate climate (79.9%),

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followed by tropical climate (15.4%) (Table 5).

Table 5. Sample distribution by climate of origin.

Frequency (%)

Tropical (A)

15.4

Arid (B)

4.1

Temperate (C)

79.9

Continental (D)

0.6

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Climate of origin

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The results regarding the users’ physical activity, health status and time spent inside the building are shown in Figure 4. The majority of the respondents practice physical activity one to three times a week, in terms of health status felt “as usual” and spent less than 30 minutes

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in the building.

a)

b)

c)

ACCEPTED MANUSCRIPT Figure 4. Sample distribution according to: a) physical activity; b) health status; and c) waiting time.

4. THERMAL COMFORT MODELS

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4.1 PMV-PPD model

The standard ISO 7730 [33] suggests three categories (A, B and C) to assess the whole body thermal comfort through PMV or PPD indices. Alongside these, the local discomfort

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must also be appraised by PD indices, which reflect the percentage of dissatisfied people due to unwanted cooling or heating of one particular part of the body, namely due to radiant

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asymmetry, vertical air temperature difference, warm or cool floors and draught. All the parameters have their own defined limits that must be checked simultaneously, in each category.

For each measurement, the mean PMV and the corresponding PPD were calculated to

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assess the whole body thermal comfort (Figure 5). Generally, the PMV value was negative, indicating cold thermal sensations. The mean PMV value ranged between -1.81 and 0.15, which led to a maximum PPD value of 68%, in building BI during the morning. In both

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buildings, the mean PMV attained in 50% of the measurements is outside the limits of ISO 7730 category C. On the other hand, the requirements of category A, the narrower, were

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accomplished in 10 and 30% of the measurements in BI and BII, respectively.

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Figure 5. Mean PMV versus PPD for arrivals (AM) and departures (PM)

Figure 6 depicts the results of the PD due to warm or cool floors and due to vertical air temperature difference. The PD due to radiant asymmetry and the draught rate were always null and thus are not plotted in the paper. The assessment of local thermal discomfort showed

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that the limits imposed by ISO 7730 were always accomplished. The only exception occurred in the PD due to warm or cool floors in witch 1 measurement was above the limit of category

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B but below the one of category C.

Figure 6. PD due to warm or cool floors (tf) and due to vertical air temperature difference (△t a,v) for arrivals (AM) and departures (PM).

ACCEPTED MANUSCRIPT 4.2 EN 15251 and ASHRAE 55 adaptive models The adaptive model proposed by EN 15251 assumes that the operative temperature varies according to the outdoor running mean temperature, which is an exponentially weighted running mean of the daily mean external air temperature of the previous 7 days. This model

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also includes three different indoor operative temperature limits, which correspond to a certain expected percentage of dissatisfied people (category I: PPD < 6%; category II: PPD < 10%; category III: PPD < 15%). Figure 7 presents the mean operative temperature attained,

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separately for morning and afternoon campaigns. According to this model, in both buildings, 30% of the records, which correspond to 6 measurements, are below the comfort zone. 5 of

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these measurements occurred during the morning. If one focus on category B (normal level of expectation that should be used for new buildings and renovations), 60% of the records are

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within the limits of comfort in building BI and this value decreases up to 40% in BII.

Figure 7. EN 15251 adaptive model for arrivals (AM) and departures (PM) – optimal operative temperature (Too )

In the adaptive model proposed by ASHRAE 55, the operative temperature of comfort is dependent on the outdoor mean monthly temperature, which was derived using data from the

ACCEPTED MANUSCRIPT previous 30 days. This standard establishes 2 limits that correspond to a theoretical 90% and 80% acceptability of the indoor thermal environment. Figure 8 depicts the results for the 2 buildings. According to this model, only 3 records (2 in building BII and 1 in BI, all in the morning) meet the limits for 80% acceptability. Overall, one may say that the adaptive models

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are less restrictive than the PMV-PPD model, which is in line with previous research [47, 48].

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5. DISCUSSION

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Figure 8. ASHRAE 55 adaptive model for arrivals (AM) and departures (PM)

The results attained in the fieldwork and the information gathered in the survey were

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combined and used for discussing the adequacy of the traditional comfort models to this kind of buildings.

Figure 9 portrays the strength of the association between the average PMV values and the mean thermal sensation (MTS), as well as their relation to the operative temperature (To).

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b)

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a)

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Figure 9. PMV and MTS vs. operative temperature: a) building BI; b) building BII.

It can be clearly observed the offset of the MTS in comparison to the PMV values, for the same operative temperature. This difference is more marked in building BI. Concerning the linear regression models, the coefficient of determination, R2, is higher in building BII, while

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in BI a wide dispersion of the results can be observed. The boxplot representation shows that the thermal sensations are slightly less dispersed than the PMV values. Moreover, these values mismatch considerably. The operative temperature leading to neutral MTS was 17.2 ºC

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in building BI and 20.6 ºC in BII, whilst the PMV equivalent was 25.4 ºC and 25.0 ºC. An attempt to identify the influence of the national origin was made by analyzing the

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MTS and the MTP, separately for respondents from tropical (type A) and temperate (type C) climates. The choice for these two climates was based on the number of respondents as their sum corresponds to 95% of the total (Table 5) Figure 10 displays the results.

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a)

b)

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Figure 10. Frequency by climate type: a) mean thermal sensation; b) mean thermal preference

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The differences in MTS are more evident. A clear trend for cooler sensations among respondents from a tropical climate is noticed, while a drift for the positive side of the scale, warmer perceptions, is observed in originating from temperate climate countries. In what concerns the MTP, the data shows that the majority of the respondents voted for an

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unchanged environment in both data-sets, in line with previous works [32, 39]. These results confirmed the possibility of national origin being an important factor that may bias the overall analysis presented in Figure 9. This effect was more obvious in

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respondents from tropical climates and, therefore, a correction of the results was tested. To that end, in each building, the campaigns in which the percent of respondents from tropical

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climates was higher than 40% were deleted. This criterion was selected after a previous sensitivity analysis in which the positive impact of the correction was always observed, however, using this value more robust data subsets were attained. The application of this correction resulted in higher correlation between the parameters, in building BI, and identical in BII (Figure 11).

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b)

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a)

Figure 11. Corrected PMV and MTS vs. operative temperature: a) building BI; b) building

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BII.

For these corrected regressions, the neutrality of the mean thermal vote (MTS = 0) is found at 17.7 ºC. and 20.6 ºC, in BI and BII, respectively. On the other hand, the neutrality

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through the PMV regression lines was 25.8 ºC in BI and 24.7 ºC in BII. A slightly narrower gap between the mean thermal sensation votes and the predicted mean votes is now observed when compared to the original ones.

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The impact of national origin is also observed when one analyzes the relation between MTS and MTP. Figure 12 expresses the results of this relation for each building, with and

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without the correction. The coefficient of determination, R2, increases when the correction is applied. Moreover, the results revealed that a preference for neutral or slightly warmer thermal environment is associated to positive mean values of the thermal sensation. However, the correlation found and the rather small spread of the results make it impossible to draw definite conclusions.

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Figure. 12. MTP versus MTS: a) building BI; b) building BII; c) building BI with the

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correction; d) building BII with the correction.

Figure 13 shows the relation between MTP and the operative temperature when the correction is applied. The coefficient of determination indicates a good correlation between these parameters. As expected, with the rise of the operative temperature there is a preference for cooler environments. In both buildings occupants voted in majority to no change in the thermal environment.

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building BII with the correction.

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Figure 13. MTP versus operative temperature: a) building BI with the correction; b)

Finally, it was tested the relation between PMV and the MTS. Figure 14 depicts the results. A mismatch of the PMV model is obvious, especially in building BI. While most of

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the respondents classified the thermal environment as neutral or slightly warm, the PMV model ranged between -2.0 and 0.0 in building BI and between -1.5 and 0.5 in BII. Therefore, the PMV model tends to classify the thermal environment as being cooler than the actual

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thermal sensation of the users. This kind of problems were also reported previously [49, 50].

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Fig. 14. PMV versus MTS: a) building BI with the correction; b) building BII with the correction.

The waiting time, the number of travel companions, the health status and the physical

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activity were tested for possible correlation with the thermal tolerance (TOL) and the thermal acceptability (TSA). A Spearman’s rank matrix was computed, using the average measured values and the individual responses for each campaign and for buildings BI and BII

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separately. No significant correlations were found between health status, physical activity and number of travel companions. Only waiting time (WT) arose with a moderate, but statistical

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significant correlation with thermal tolerance (TOL) and with thermal acceptability (TSA). Table 8 summarizes the findings. Less tolerance and acceptability are expected with increasing waiting time in the buildings, in agreement with [46].

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Table 8. Spearman’s rank matrix’ relevant correlations Correlations

Building

BI

BII

R

α

R

α

WT - TSA

0.205

0.000

0.215

0.004

WT - TOL

0.212

0.000

0.154

0.038

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Variables

6. CONCLUSIONS

The lack of studies regarding the thermal comfort assessment in cruise terminal buildings, sparked this research. A methodology supported by field measurements and questionnaires was successfully implemented and the following conclusions were drawn: •

The user survey demonstrated that the acceptability of the studied spaces was high since the questionnaires resulted in MTS= 0.368 and MTP= 0.105 in BI and an MTS= 0.250 and MTP= 0.031 in BII;

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The adaptive models provided a broader acceptance of the measured environmental conditions. This was in line with the broader acceptance demonstrated by the users. Above 60% wanted “no change”, in both buildings.

•

The comparison of the user survey with the analytical comfort model found that PMV

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values were in their clear majority lower than correspondent MTS values for substantial ranges in both buildings. Operative temperatures for neutrality met 17.7ºC in BI and 20.6ºC in BII with MTS votes. These are lower by 8.1ºC and 4.1ºC,

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respectively, in comparison with the calculated PMV. The model therefore overestimates the cooling sensation. At the same time, the variables associated with

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local thermal discomfort met comfort limits every time;

The PMV-MTS correlation presented moderate to low correlation factors, which can be explained by 2 factors:

o Increasing waiting times in the terminals lead to increasing thermal stress and

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less personal tolerance. As the waiting time associated with the majority of the responses was reduced, the users had a broader acceptance of the thermal environment.

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o Users originating from several countries with different climate types made part

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of the sample. A clear trend for a cooler environment sensation for tropical type climate originals and a tendency for the warmer side of the scale in MTS for the temperate type climate ones was found.

7. ACKNOWLEDGEMENTS This article has been developed from the results obtained within the framework of the SUDOE Stop CO2 project and the CONSTRUCT project.

ACCEPTED MANUSCRIPT SUDOE Stop CO2 is a project co-funded by the Interreg Sudoe Programme through the European Regional Development Fund (ERDF). Project POCI-01-0145-FEDER-007457 - CONSTRUCT - Institute of R&D In Structures and Construction is funded by ERDF funds through COMPETE2020 - Programa Operacional

Fundação para a Ciência e a Tecnologia.

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Highlights:

Evaluation of indoor thermal comfort in cruise terminal buildings;

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A total of 572 questionnaires and 20 independent field measurements were

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•

carried out;

Greater demand by passengers with increasing waiting time;

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Comfort was met more frequently with the adaptive models.

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•