A discussion about thermal comfort evaluation in a bus terminal

Accepted Manuscript

A discussion about thermal comfort evaluation in a bus terminal Vitor E.M. Cardoso , Nuno M.M. Ramos , Ricardo M.S.F. Almeida , Eva Barreira , Joao ˜ Poc¸as Martins , M. Lurdes Simoes ˜ , Lu´ıs Sanhudo PII: DOI: Reference:

S0378-7788(17)33992-0 10.1016/j.enbuild.2018.03.013 ENB 8399

To appear in:

Energy & Buildings

Received date: Revised date: Accepted date:

8 December 2017 26 February 2018 5 March 2018

Please cite this article as: Vitor E.M. Cardoso , Nuno M.M. Ramos , Ricardo M.S.F. Almeida , Eva Barreira , Joao ˜ Poc¸as Martins , M. Lurdes Simoes ˜ , Lu´ıs Sanhudo , A discussion about thermal comfort evaluation in a bus terminal, Energy & Buildings (2018), doi: 10.1016/j.enbuild.2018.03.013

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Highlights:



Evaluation of a bus terminal building using questionnaires and field measurements; Standardized comfort assessment methods overestimated the cooling sensation;



The thermal preference method provided a SET* comfort range in line with the

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thermal acceptability of the respondents.

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

ACCEPTED MANUSCRIPT

A discussion about thermal comfort evaluation in a bus terminal Vitor E. M. Cardoso (1)*, Nuno M. M. Ramos (1), Ricardo M. S. F. Almeida (1),(2), Eva Barreira (1)

, João Poças Martins (3), M. Lurdes Simões (1), Luís Sanhudo (3)

(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. (3) CONSTRUCT-GEQUALTEC, Faculdade de Engenharia (FEUP), Universidade do Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal. *

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Corresponding author: E-mail: [email protected]

ABSTRACT

Transport stations are distributive hubs composed of transient spaces, often not fully indoor, where most users spend time waiting to travel or waiting for travelers. The aim of this article

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is to present a comparison between thermal comfort evaluation methods applied in a free

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running bus terminal located in a mild climate country. Data was collected in field measurements and surveys were performed on 240 passengers, focusing warm season

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operation conditions. The collected information allowed for the analysis of the comfort

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conditions of the station according to the following comfort models: PMV-PPD, aPMV, and the adaptive models defined in the ASHRAE 55 and EN 15251 standards. A comparison

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between the results and the thermal preference (MTP) and the thermal sensation (MTS) expressed in the ISO 10551 subjective scales was performed. It could be concluded that the PMV-PPD and aPMV models overestimated the cooling sensation. The ASHRAE 55 and EN 15251 adaptive approach, although more permissive, still was not totally in line with the thermal sensation of the respondents. An alternative approach based on the correlation between SET* and dissatisfied voters established through the thermal preference method provided a wider comfort range that appears, in this case, to be adequate.

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Keywords: Transport station, Thermal comfort, Steady-state models, Adaptive models, Questionnaire, Semi-outdoor environment, Transient spaces

1. INTRODUCTION

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The human comfort in transport stations is a concern for practitioners and researchers, reflected in different studies conducted on the subject [1-5]. Transport stations are distributive hubs composed of transient spaces, often not fully indoor, where a rising number of users spend time waiting to travel or waiting for travelers. The intelligent design and management

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of transport station buildings can produce comfortable environments for the users with a positive impact on energy efficiency [6]. Hence, a precise knowledge of the environmental conditions desired by the users is needed.

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The specific features of transport station buildings and their users imply a careful strategy to cope with the relevant influencing factors. The outdoor climate, the nature and purpose of

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the spaces and the time spent in them by the users are factors referred in literature [7, 8] that can be especially relevant. The outdoor climate is a relevant factor for indoor thermal

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comfort, mainly in free-running facilities [9] and it also impacts the individual perception of

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comfort based on cultural and reactive aspects [8]. For different climate types the accustomed populations tend to adapt and accept different thermal conditions as neutral [10, 11]. The

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nature and purpose of the occupied spaces influence expectations and thermal comfort or stress. The transport station spaces with user presence can fit different categories regarding their nature, including indoor spaces, outdoor urban precincts, semi-outdoor areas and the specific case of underground zones. The research targeting these different spaces shows different levels of development. A large number of studies on the comfort of indoor spaces has been developed, including field measurements [12], that have demonstrated the

ACCEPTED MANUSCRIPT applicability of the different thermal comfort models. Semi-outdoor areas and underground zones, on the other hand, are not so frequently targeted by comfort studies but they are relevant for the full understanding of transport facilities. Nevertheless, examples of studies about these typologies can be found in literature, showing that the application of thermal comfort models requires a careful calibration when studying semi-outdoor areas [13] or

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underground zones [1]. The purpose of a relevant part of the areas in transport stations fits the profile of transitional spaces [14]. This adds an additional layer of complexity to the study because the user behavior diverts from the typical sedentary behavior observed in offices and homes [15]. The purpose also impacts the exposure time to environment. This is very relevant

acclimatization occurs over time [16, 17].

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since different periods of exposure lead to different environmental perceptions as

The investigation available on semi-outdoor environments is scarce. So is the case of

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transitional spaces [14]. The building studied in this paper falls under this purpose and nature. Semi-outdoor configurations have a mixture of characteristics of free-running buildings (no

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HVAC systems) and outdoor areas, prevailing higher thermal tolerance [18]. A specific aspect of transitional or transient spaces is the reduced time spent by most of their users, a trait

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shared with outdoor areas [19]. Little time spent equals to steady state of users not always

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being met. Steady state models tend to overestimate discomfort in these cases [19]. Alliesthesia [20] is another variable hard to account in this kind of environment [21]. In a

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field survey in an Amsterdam museum [22] it was found a significant alliesthesial response by the users and the existence of a buffer interval from the time the occupants enter the monitored space. Users preserved part of their perception and association with the outdoor environment for the first 20 minutes indoors. In mechanically ventilated airport terminals, in the United Kingdom, a preference for cooler temperatures and less sensitivity to temperature changes by passengers was found, in

ACCEPTED MANUSCRIPT comparison with workers [2]. The view of the terminals as transition spaces brought wider adaptation potential. Thermal comfort at a given temperature is dependent on preceding exposed temperatures. This effect known as relative evaluation tendency was detected in transitional spaces, with laboratory and field experiments in summer, fall and winter seasons, in Yokohama, Japan

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[23]. The response amplitude of thermal comfort votes was higher in the studied train station facilities. Although this particular study focused on short timeframes thermal history impact, 24h [24] and seasonal [25] thermal memory evaluation was also studied. A study comparing free-running shopping malls and mechanically ventilated department stores in the same city

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concluded similarly [26] on the propensity to evaluate HVAC environments more strictly. The aim of this research is to present a comparison between thermal comfort evaluation methods applied in a free running bus terminal located in a mild climate country. The data

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collected in field measurements and passenger surveys was analyzed to pursue the following objectives:

and adaptive models.

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- Characterize the thermal comfort of a bus terminal building using steady-state models

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- Correlate the analysis with the responses of the users;

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- Study the acclimatization and adaptation of users in transient spaces; - Determine the suitability of each model in the prediction of the thermal responses of

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users in free running bus terminals.

2. THERMAL COMFORT MODELS AND INDICES

ACCEPTED MANUSCRIPT Based on past fieldworks and relevant results, several indices were chosen to assess the indoor thermal environment of the free running bus terminal in study. The selection includes indices derived from human energy balance models such as the PMV [27], PET [28] and SET* [29], and adaptive models like aPMV [30] and the ones included in ASHRAE 55 [31] and EN 15251 [32] standards.

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The study of organic thermal comfort in indoor environments and large group of answers made path for the steady state model of comfort vote prediction – PMV. The model is described in the ISO 7730 [33] standard, including whole body thermal comfort with PMVPPD indices and local discomfort PD indices. These PD indices assess the percentage of

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dissatisfied people due to involuntary cooling or heating of specific parts of the body, either from radiant asymmetry, air temperature differences and draught. For each of the 3 comfort categories, simultaneous whole and local thermal comfort limits of parameters must be met.

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The PET index is derived from a complete heat balance model of the human body [28, 34], based on the Munich Energy balance for Individuals. PET is equivalent to the air

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temperature at which the body heat balance is preserved with core and skin temperatures identical to those under the conditions being evaluated [28]. The equivalent temperature

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provided assumes 50% relative humidity at 20 ºC and an air velocity of 0.1 m/s. For the

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reference person settings, of 80 W of metabolism for light activity and 0.9 clo of clothing insulation, thermal sensation comfort ranges, PMV interval of [-1.0; 1.0], corresponds to PET

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fluctuating from 18 to 23 ºC [35, 36]. This implies that the index is not constrained by singular attitudes. Although the variables used being the same, relevant differences from the two-node model [37] used in SET* are introduced by the calculation of the sweat rate and division of covered and uncovered body surface when considering heat flows [28]. SET* is the dry-bulb temperature of a theoretical environment at 50% relative humidity for subjects wearing clothing that would be standard for the given activity in the real environment.

ACCEPTED MANUSCRIPT Clothing insulation values are dependent on the activity level. This model differs from PET in the structure of the heat balance models and in the definition of reference conditions of clothing insulation, activity, relative humidity, temperatures and air speed[38]. Thermal comfort, when assessed with the initial considerations, 50% relative humidity, less than 0.1 m/s average air speed, mean radiant temperature equal to mean air temperature, 1.0 met (104

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W) of metabolism and 0.6 clo of clothing insultation, corresponds to a SET* range of 17 to 30 ºC.

The objective of the aPMV model is to consider subjective factors in thermal comfort assessment, psychological and behavioral among others, and not only the heat balance of the

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human body [39]. This model differs from the original PMV mainly by the application of the Black Box method [30] and by establishing a mathematical model for better prediction of outputs by inputs. For thermal comfort assessment the inputs are the responses to the

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questionnaires by the users. Based on the adaptation of people to higher temperatures in summer and lower temperatures in winter, the model compiles adaptive coefficients in the

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pursue of correcting the overvaluation of warmness in hot seasons and coolness in cold seasons [40]. Previous studies on this subject [41, 42] highlighted the importance of

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expectation to justify the need for the introduction of correction factors in some applications

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of the PMV model.

Limit values for the operative temperatures are defined as a function of outdoor

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temperatures in the EN 15251 and ASHRAE 55 models. The first using an exponentially weighted running mean of the daily mean outdoor air temperature of the seven preceding days and the second relying on the outdoor mean monthly temperature. The expected percentage of dissatisfied users defines the EN 15251 thermal comfort limits, while in ASHRAE 55 they result from the presumed percentage of acceptability by occupants.

ACCEPTED MANUSCRIPT Table 1 summarizes the thermal comfort models applied in the present work and the input parameters considered in each one. Table 1. Thermal comfort and input parameters Indices Type

PMV Steady-state

aPMV

EN 15251

ASHRAE 55

x

Adaptive

x

x

x

x

x

x

x

PET

SET*

x

x

x

x

Physical

Indoor air temperature

x

Indoor relative humidity

x

Air velocity

x

x

Mean radiant temperature

x

x

Metabolic rate

x

x

Clothing insulation

x

x

Outdoor temperature

x

x

x

x

x

x

x

x

x

x x

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Personal

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Input parameters

Several studies conducted in transport stations applied different thermal comfort models, finding relevant aspects that are specific to these buildings. Those studies also allowed for a comparison of the tested thermal comfort models.

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A fieldwork [3] in a railway station in China found the aPMV index to be more suitable

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than the PMV model in the prediction of the thermal comfort of passengers. Growing demand for thermal comfort with the increase of waiting time was also highlighted by this study.

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Surveys and measurements in Seoul subway stations [4] concluded in a broad temperature

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range, for an 80% acceptability of users, when assessed through SET*. The low correlation found between objective and subjective retrieved data was justified by the transitional purpose

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of transport stations and the short periods of time users spent indoors. A thermal comfort study during the four seasons, in four semi outdoor spaces in Tokyo,

pointed to the three times wider tolerance of occupants in these environments than indoors [43]. It was found SET* to be the best predictor of thermal sensation in comparison with PMV and ET* [37] models, particularly in HVAC absent spaces. In the studied spaces, the 20% discomfort range was approximately 3.5 times broader than the one given by the measured PPD.

ACCEPTED MANUSCRIPT The PET index is mainly used in the assessment of outdoor thermal comfort [44, 45]. The index was used in an indoor environment highly dependent on outdoor climatic conditions, a free-running rail terminal in India [5]. As expected, it was stated that with almost identical mean radiant temperature and indoor air temperature the use of the PET loses significance. Still, neutral temperatures found through actual mean votes and ASHRAE 55 model showed

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their underestimation by the latter, with an offset of approximately 4 ºC.

3. METHODOLOGY 3.1 Case study

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The fieldwork underwent during June 2017 in a bus station in Porto, Portugal. This station articulates most of the regional bus connections of the city. With a ground area of approximately 5000 m2, the station has 15 bus platforms, several administrative offices, small

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shopping stores, public toilets and a cafeteria. The volume of the building is about 25000 m3 and the average indoor height of the main platform is 5 m.

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The bus station occupies the ground floor of an office building. It has two large entrances at the street level for vehicles access, two smaller entrances for people and several air inlets,

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including a circular skylight with a diameter of approximately 6.5 m. The facility also has a

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mechanical ventilation system to guarantee the indoor air quality (Figure 1).

Figure 1. Indoor and outdoor views of the studied facility

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3.2 Equipment Relevant parameters to assess global thermal comfort – air temperature, relative humidity, mean radiant temperature and air velocity –

and local thermal discomfort – radiant

asymmetry temperature, floor temperature and temperature at different body levels – were

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measured in accordance with ISO 7730 [33] and ASHRAE 55 [31] specifications. The equipment used during the test campaign to evaluate comfort complies with the specifications of ISO 7726 [46] [46]. Table 2 presents the parameters that were measured as well as the probes height at the site, their range, resolution and accuracy of. The data read by the probes

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was stored in a data logger for further processing. Exterior air temperature and relative humidity were registered by a weather station in the vicinities.

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Table 2. Description of the different probes that were used 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

Temperature at ankle level [Tk] (1)

0.10 m

-10 to +100 °C

0.01 °C

-0.08 to +0.19 °C

(1)

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

Parameter

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Air temperature [Ta]

(1)

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Floor temperature [Tf]

(1)

Temperature at head level [Th]

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Temperature at abdomen level [Tb] (1)

(1) Heights in accordance with ISO 7726 [46] recommendations

3.3 Procedures The very large area of the main hangar imposed a preliminary measurement campaign to

select the representative waiting area. A total of five different locations were chosen (Figure 2). Table 3 presents some statistic measures: sample means (mean), standard deviations (std.

ACCEPTED MANUSCRIPT dev.), and coefficients of variation (C.V.) of air temperature (Ta), relative humidity (RH), air velocity (vair) and radiant temperature (Trad).

S5

S3

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S1

S4

S2

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2 9

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Figure 2. Locations evaluated in the preliminary analysis

Variables

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Table 3. Descriptive statistics of the preliminary data Parameter

S2

S3

S4

S5

23.76

23.38

23.71

23.58

23.80

Std. Dev.

0.21

0.17

0.04

0.13

0.02

C.V. [%]

0.87

0.73

0.16

0.55

0.08

Mean

58.58

59.33

59.39

58.72

57.98

Std. Dev.

0.65

0.46

0.37

0.82

0.26

C.V. [%]

1.12

0.77

0.62

1.40

0.45

Mean

0.13

0.10

0.13

0.30

0.14

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Mean

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Ta [ºC]

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RH [%]

vair [m/s]

Trad [ºC]

Locations

S1

Std. Dev.

0.09

0.11

0.14

0.13

0.11

C.V. [%]

67.84

114.02

104.51

43.57

78.64

Mean

23.52

23.83

23.90

23.38

23.30

Std. Dev.

0.18

0.13

0.10

0.22

0.16

C.V. [%]

0.76

0.53

0.42

0.93

0.70

No relevant differences emerged among the dataset, except for the air velocity. The coefficients of variation obtained for this parameter were very high, which results from its inherent variability. In most locations air velocity tended to vary between 0 and 0.2 m/s, but

ACCEPTED MANUSCRIPT in location S4 the average value was 0.3 m/s. That was related to the proximity with one of the main entrances. However, this was not one of the prevailing locations, because only a few buses stopped in that parking area. Since no differences existed between the other four locations, the selection of the representative one was based on obtaining a large number of responses in the questionnaire. For that reason, position S3 was targeted for further study as

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the vast majority of passengers stood or lingered in this waiting area that is alongside small stores, ticket booths and bus platforms. Figure 3 shows the relation between the operative temperature (Figure 3a) and the PMV index (Figure 3b) and the air temperature in the five positions. The effect of air velocity in position S4 is once again noticeable as its PMV value is

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lower than the one found in the other positions. The good agreement between air temperature

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and operative temperature confirms the reduced effect of radiation.

a)

b)

Figure 3. a) Air temperature versus operative temperature; b) Air temperature versus

PMV.

Logging intervals of 60 seconds for periods of 20 minutes were measured in 3 different parts of the day – morning (AM), lunchtime (LT) and afternoon (PM) – during the 5 studied

ACCEPTED MANUSCRIPT days, in a total of 15 measurements for global thermal comfort and 15 for local thermal discomfort variables. An average of 48 passengers per day and 16 passengers per single measurement were questioned, totaling 240 filled surveys. Only Portuguese originals were enquired. To avoid the casual influences by the bus and the previous thermal sensation in the buses, only passengers arriving at the station were selected for the questionnaire and the

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sampling location was well away from the area affected by the exhaust heat and smell.

3.4 Exterior climate

Porto is located in the North of Portugal, in the Atlantic coast. It has a warm-summer

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Mediterranean climate, according to the Köppen-Geiger climate classification [47], with an average temperature of 9.5 ºC in January and 20.8 ºC in August. During the summer months, in average, temperature ranges between 15 and 25 ºC, approximately. Figure 4 presents a

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complete description of the climate of Porto, based on the historical data made available by

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IPMA [48].

Figure 4. Annual outside air temperature for the city of Porto (Portugal)

ACCEPTED MANUSCRIPT The experimental campaign was carried out in the beginning of the summer period, between June 20 and July 1. Figure 5 shows the fluctuation of the outdoor air temperature,

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highlighting the periods in which the measurements took place.

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Figure 5. Outdoor air temperature during the measurement period

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3.5 Questionnaire

Occupants were enquired with a multiple-choice questionnaire structured for quick and

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intuitive filling. The questionnaire was divided in 3 distinct parts: sample characterization, thermal impression, and worn clothing.

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Sample characterization focused in personal questions on gender, age, height, weight and

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waiting time inside the building. The questions were open ended as the respondents did not have to choose from premade intervals. Thermal impression of users was examined through thermal sensation (MTS) and thermal

preference (MTP) and thermal stress acceptability (TSA) according to the subjective scales suggested in ISO 10551 [49]. Clothing insulation was analyzed in consonance with ASHRAE 55 [31] and ISO 7730 [33] presets. Different clothing options for the distinct body parts were available for ticking.

ACCEPTED MANUSCRIPT Individual questionnaire sum value of clothing insulation was used for data treatment. It was presumed a 1.2 met value for the metabolic rate of occupants, since only relaxed standing and sitting waiting passengers were surveyed [31, 33].

4. QUESTIONNAIRE RESULTS AND ANALYSIS

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A total of 240 individual questionnaires were taken up, 110 males and 130 females. The results of the descriptive statistics concerning the age, weight and height of the sample are presented in Table 4. The assessment of the clothing insulation was made through the determination of the clo value (Table 5). The results revealed similar distributions of the

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clothing insulation in the 3 periods of the day and in the 5 days of survey.

Table 4. Statistical information on age, weight and height. Age [years]

Weight [kg]

Female

Male

Male

Total

Female

Male

Mean

30.0

27.7

32.7

66.7

59.9

74.6

169.3

164.0

175.5

Maximum

70

66

Minimum

11

16

70

120

90

120

191

180

191

11

36

40

36

152

152

156

Std. Dev.

13.4

11.3

15.1

12.5

8.6

11.8

9.0

5.9

7.8

C.V. [%]

44.5

41.0

46.1

19.0

14.4

15.8

5.0

3.6

4.5

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Total

Height [cm]

Female

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Total

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Measure

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Table 5. Clothing insulation (clo) descriptive statistics for different periods of the day. Period of the day

ID of the day

AM

LT

PM

01

0.38

0.31

0.31

02

0.41

0.37

0.40

03

0.41

0.41

0.42

04

0.34

0.53

0.46

05

0.58

0.54

0.50

Mean

0.45

0.46

0.43

Std. Dev.

0.16

0.18

0.17

C.V. [%]

38

31

31

ACCEPTED MANUSCRIPT The results of the individual thermal sensation and preference by gender are displayed in Figure 6. Overall, the mean thermal sensation (MTS) was 0.633, pointing to a slightly warm environment. A slight difference between men and women was also observed, as men tend to evaluate the same environment as warmer (MTS = 0.691 versus MTS = 0.585). This difference was already emphasized in previous works [50, 51]. The answers regarding thermal

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preference are in line with the thermal sensation, with a mean thermal preference (MTP) of 0.325, which corresponds to a preference for a slightly cooler environment. Nevertheless, one must stress that the range of thermal sensation and thermal preference votes was wide within the entire sample, which can bias the conclusions based on a single overall MTS and MTP

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average value.

a)

b)

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Figure 6. Individual thermal vote by gender: a) thermal sensation; b) thermal preference.

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Figure 7 shows the relation between MTS and MTP. It can be observed that the preference

for no change in the thermal environment corresponds to a slightly positive thermal sensation. Other authors already reported this response by users [22, 52].

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Figure 7. MTP versus MTS.

5. APPLICATION OF THERMAL COMFORT MODELS 5.1 PMV-PPD– ISO 7730 and aPMV models

The plot representation of the PMV-PPD model, proposed by ISO 7730 to assess the

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whole body thermal comfort, can be found in Figure 8. According to this model, 86.7% of the

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measurements are outside the comfort limits of category C, the less restrictive comfort category (-0.7 < PMV < +0.7). The remaining 13.3% are periods in which even the limits of

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category B are accomplished, and correspond to one morning and one afternoon

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measurements. The record that revealed the most uncomfortable situation occurred during the morning period, with a PMV value of - 1.70. The PMV value closest to thermal neutrality was

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0.33. On the other hand, the highest PMV value was 1.01 and occurred in the afternoon. Overall, this apparently uncomfortable scenario did not reflect in the thermal preferences of the respondents, since 39.6% voted for no change in the thermal environment (Figure 6). A detailed analysis of daily variation of the PMV revealed that it constantly increased throughout the day, as expected.

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Figure 8. Mean PMV versus PPD for AM, LT and PM periods.

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ISO 7730 also establishes three comfort categories when assessing local thermal discomfort. The results revealed that, in this study, local thermal discomfort was not an issue as in the entire dataset even the limits imposed by category A have been fulfilled, except for

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the draught rate. The percentage of dissatisfied due to warm and cool floors and due to vertical air temperature difference are depicted in Figure 9. The percentage of dissatisfied due

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to radiant asymmetry was approximately null throughout the entire study. In the case of draught rate, the measured values ranged from 3.5% to 23.2%, in compliance with the limits

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imposed by category C.

a)

b)

ACCEPTED MANUSCRIPT Figure 9. PD due a) to warm or cool floors (tf) b) to vertical air temperature difference (Δta,v). The application of the aPMV model [30] requires the calculation of the adaptive coefficients by the least squares method. The results attained for this coefficient were -1.02 and 0.77, for cool conditions and for warm conditions, respectively. The coefficient for cool

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conditions was found to be higher, since the disparities between the MTS and the PMV values were more significant in this zone of the thermal sensation scale. These values surpassed others found in the literature, either for bus terminal buildings [3] or other types of buildings [53, 54].

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According to the questionnaires, the respondents demonstrated great capacity for thermal adaptation but the aPMV model was unable to fully identify it. Figure 10 displays the results of the aPMV model and the corresponding MTS values versus the operative temperature (To).

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The original PMV values and linear regressions were added for further understanding.

Figure 10. Operative temperature versus MTS – aPMV – PMV

The graph provides valuable information as the offset between the two comfort models and the MTS can be clearly identified. In fact, both models pointed to a colder thermal

ACCEPTED MANUSCRIPT sensation than the results of the questionnaire. Nevertheless, the aPMV model shows a better performance for lower operative temperatures, while the PMV values are closer to MTS when the operative temperature is higher than 26 ºC. Table 6 further documents the thermal comfort region and the corresponding limits. The ranges of ±0.50 and ±0.85 were selected as they

Table 6. Operative temperature for MTS – PMV – aPMV Thermal vote scale Variable

-0.85

-0.50

0.00

0.50

0.85

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correspond to 90% and 80% thermal comfort acceptability [55, 56].

± 0.85

± 0.50

ΔTo (ºC)

T o (ºC) 14.9

16.9

19.8

22.6

24.6

9.7

5.7

PMV

22.9

24.1

25.8

27.5

28.7

5.8

3.4

aPMV

19.5

22.0

25.5

29.0

31.5

12.1

7.1

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MTS

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According to the respondents, the thermal neutrality occurs at an operative temperature of 19.8 ºC. The PMV and the aPMV methods pointed for higher neutral operative temperatures

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(25.8 and 25.5 ºC, respectively). Concerning the range of thermal vote between ±0.85, the PMV model returned a temperature interval of 5.8 ºC, while this value increased up to 12.1 ºC

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when using the aPMV model. The MTS was in between with a range of 9.7 ºC.

5.2 EN 15251 and ASHRAE 55 adaptive models

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The adaptive models, by definition, assess the thermal comfort of individuals less restrictively [9, 57]. These models were derived for indoor spaces and, thus, some mismatch is expected. A proposal for correcting the existing models to fit the responses of the subjects is a possible next step, however, additional data is required to provide robustness to the model. Figure 11 and Figure 12 show the plot of the surveys separately for morning, lunchtime and afternoon periods. According to the EN 15251 adaptive model, 3 surveys (2 in the

ACCEPTED MANUSCRIPT morning and 1 during lunchtime) were evaluated as uncomfortable, since the average operative temperature was below the lower limit of the less restrictive comfort category. Using ASHRAE 55 adaptive model, only 1 morning survey presented an average operative temperature below the 80 % acceptability inferior limit, however, on the other hand, 2 surveys (1 during lunchtime and 1 in the afternoon) are now above the upper limit of the operative

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temperature.

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Figure 11. EN 15251 adaptive model for AM, LT and PM periods

Figure 12. ASHRAE 55 adaptive model for AM, LT and PM periods

According to both ASHRAE 55 and EN 15251 methodologies, comfort is provided in 80% of the measurements. As seen in the PMV analysis, an increase of the operative

ACCEPTED MANUSCRIPT temperature is detected as the day passes. ASHRAE 55 tends to evaluate the measurements consistently in the warmer side of the comfort zones in comparison with EN 15251. This judgment was found to be more in line with the individual sensation votes of the passengers.

5.3 PET and SET* indices

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The special characteristics of this building motivated the evaluation of the applicability of other comfort indices. Thus, in order to discuss the thermal neutrality and comfort ranges, the PET and SET* were determined using the RayMan software [58]. As expected, due to the small difference between indoor air temperature and indoor mean radiant temperature, the

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PET is similar to the indoor air temperature (Figure 13a). Larger differences are observed for the SET* model. The higher the air temperature the greater the offset between SET* and PET

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values. This confirms that SET* is more sensible to variations in the air velocity.

a)

b)

Figure 13. a) PET – SET*-To versus Ta; b) PET – SET*-To versus MTS.

Figure 13b plots the MTS versus the results of the PET and SET* models. According to the equations of the regression lines, the neutral temperatures are 19.6 and 19.3 ºC in PET and SET* indices, respectively. The thermal neutrality concerning the operative temperature was

ACCEPTED MANUSCRIPT quite similar (19.8 ºC). All these values are lower than the neutral operative temperatures found both with PMV and aPMV models (Tables 6 and 7). The operative temperature correlates with MTS responses slightly higher (R2 = 0.84) than PET (R2 = 0.83) and SET* (R2 = 0.79). Thus, in this case study, the use of the operative temperature presents itself as a reliable parameter to assess thermal comfort, no weaker than PET or SET*.

Temperatures (ºC)

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Table 7. Thermal vote scale limits of MTS for To, PET and SET*

-0.5

0

0.5

0.85

To

14.9

16.9

19.8

22.6

24.6

PET

14.5

16.6

19.6

22.6

24.7

SET*

14.8

16.6

19.3

22

23.8

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-0.85

In order to assess the acceptability of the thermal environment by the users and in the pursuance of a better understanding of thermal comfort ranges and limits, the percentage of

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dissatisfied voters was analyzed. Figure 14 shows the results using SET* as example since PET and To provided identical conclusions. Three methods were applied to adress

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acceptability: (i) direct thermal stress assessment (TSA) votes using EN 10551 subjective scale; (ii) satisfaction as identified with MTS = -1, 0 and 1 ; and (iii) expectation as correlated

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with MTP = -1, 0 and 1. The lack of average values in the negative side of the MTS scale

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(Figure 13b)) makes it only viable to discuss the comfort temperature upper limit. The 10% and 20% limits of thermal discomfort where added since they correspond to 90% and 80%,

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respectively, of thermal comfort acceptability.

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Figure 14. Thermal acceptance versus SET*.

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The results observed in Figure 14 show that using different methods for the evaluation of discomfortable respondents can lead to different ranges of acceptability. The SET* values

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associated with the 20% discomfort were 23.1 ºC, 24.4 ºC and 27.1 ºC for thermal sensation, direct acceptability and thermal preference method, respectively. The wider comfort range

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found on the thermal preference method compared to the thermal sensation one relates to the previously stated findings on statistical averages and standard deviations. In fact, users

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achieve comfort in a wide thermal sensation range, and for that the thermal preference

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average responses are more centralized resulting in reduced percentages of dissatisfied with

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the thermal environment than the ones refering to thermal sensation responses (Figure 6).

6. CONCLUSIONS Buildings with transportation purposes of a semi-outdoor and transient nature are not

often addressed in what concerns the thermal comfort of the users. The fieldwork that underwent in this research was performed for summer conditions and shed more light on the issue as several conclusions were extracted:

ACCEPTED MANUSCRIPT 

According to the results of the questionnaires, the relation between MTS and MTP showed that the preference for no change in the thermal environment corresponds to a slightly positive thermal sensation.



The traditional indoor thermal comfort models have proved inadequate as the PMV model, the aPMV model and the ASHRAE 55 and EN 15251 adaptive

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approaches were not totally in line with the thermal comfort perception of the users. An overestimation of the cooling sensation was found in each of these models, even after the substantial correction made by the aPMV formulation to the original PMV values.

The search for an alternative estimation of the comfort limits in this building was

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

attempted by correlating To, PET and SET* indices with MTS. It was concluded that the three indices provided comparable correlations. This is mostly due to the



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absence of direct solar radiation on the studied environment. The acceptability of the thermal environment by the users was quantified using

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three different methods, which were compared with the values of SET*. The

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results showed that the correlation of SET* with the dissatisfied voters established through the thermal preference method provided a wider comfort range that

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appears, in this case, to be adequate. From the results presented it is not possible to identify the factor (or the combination of

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factors) that influenced the deviation of subjective responses and comfort conditions from the prediction of environmental indices. However, some possible factors can be pointed. The climatic conditions correspond to a mild summer context with significant daily amplitude. The building is free-running and the usage is closer to a transient space. These factors lead to a transient state of the passengers which may differ from the base data used in the construction of the of the environmental indices.

ACCEPTED MANUSCRIPT 7. ACKNOWLEDGEMENTS This article has been developed from the results obtained within the framework of the SUDOE Stop CO2 project and the CONSTRUCT project. SUDOE Stop CO2 is a project co-funded by the Interreg Sudoe Programme through the European Regional Development Fund (ERDF).

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Project POCI-01-0145-FEDER-007457 - CONSTRUCT - Institute of R&D in Structures -

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The authors would like to thank Transdev and CVParques for providing logistic support

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and access to the tested facility.

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