Analysis of Thermal Comfort for Cycling Sport: A Case Study for

Rio de Janeiro Olympic Games

Alessandro Pezzoli

and Roberto Bellasio

Interuniversity Department of Regional and Urban Studies and Planning,

Politecnico di Torino and Università di Torino, Torino, Italy

Enviroware, Concorezzo, Italy

Keywords: Thermal Comfort, Weather, Computer Analysis, Cycling, Sport Performance.

Abstract: As well known the meteorological and the environmental parameters (as wind, air temperature, rain,

humidity, altitude, location, etc…) affect strongly the sport performance. Considering the recent literature

on this topic, it is evident how the evaluation of the thermal comfort in the athletes is a crucial subject that

has to be studied. In fact the thermal comfort of the athletes is not only linked with the sport performance

but also with the safety of the athletes themselves. For these reasons in this research it is presented an

innovative methodology to evaluate the thermal comfort of cycling athletes at the next Rio de Janeiro

Olympic Games. This analysis is carried out for the Rio de Janeiro area considering the two venues for the

cycling sport and for the two disciplines (Time Trial and Road Race). The meteorological data of two

stations representative of the racing areas have been collected for a period of 20 years. They have been

analyzed to produce the wind roses and to calculate two thermal indices: Predicted Mean Vote (PMV) and

Physiological Equivalent Temperature (PET). The results of this research show the importance of the

climatological analysis for optimizing the training and nutrition plans of the athletes.

1 INTRODUCTION

As shown in a previous paper (Pezzoli et al., 2015),

the assessment of bio-climatological conditions and

of thermal comfort in endurance sports, particularly

in road cycling, is essential not only for a proper

planning of the training program and the nutritional

plan, but also for a better evaluation of the racing

strategy or for the correct development and choice of

the materials.

Among the meteorological variables that

strongly influence the sport activity the most

important ones are temperature, wind, precipitation,

fog, atmospheric pressure and relative humidity.

In fact Brocherie et al. (2014) suggest how an

integration of the combination of all relevant

multidisciplinary data (i.e. thermal physiology,

mathematical modelling, occupational medicine,

biometeorology) would generate better application

in an ecological sport science setting with potential

impact on heat stress guideline management.

A deeper review about the emerging

environmental and weather challenges in outdoor

sports was held by Brocherie et al. (2015). The

Authors show how the Universal Thermal Climate

Index, also indicated by the abbreviation UTCI

(Jendritsky et al., 2002), promises to be, in the next

future, useful for the sport practitioners.

In fact the the operational UTCI procedure,

classified into ten categories of thermal stress

ranging from “extreme cold stress” to “extreme heat

stress” (Brode et al., 2012), appears useful. It

promises to assess the outdoor sport participants’

physiological responses to humidity and radiative

loads in hot environments, as well as to wind in the

cold.

Nevertheless Blazejczyk et al. (2012) illustrated

how, in a comparison between UTCI and other

bioclimatic indices, values most similar to those of

UTCI were found for indices derived from human

heat balance models as Physiological Equivalent

Temperature (PET). Similarly to the UTCI, PET also

is related to the equivalent temperature. The

differences between the specific values of these two

indeces result from the various structures of heat

balance models and different definitions of reference

conditions.

However Pezzoli et al. (2012) and Brocherie and

Millet (2015) show how also the Predicted Mean

Pezzoli, A. and Bellasio, R..

Analysis of Thermal Comfort for Cycling Sport: A Case Study for Rio de Janeiro Olympic Games.

In Proceedings of the 3rd International Congress on Sport Sciences Research and Technology Support (icSPORTS 2015), pages 281-289

ISBN: 978-989-758-159-5

281

Vote (PMV) can be used to characterize the thermal

comfort in sport activities (respectively for cycling

and tennis).

As shown by Brocherie and Millet (2015) the

WBGT is indicated by numerous leading sports

federations (e.g., Fédération Internationale de

Football Association [FIFA], International

Association of Athletics Federations [IAAF],

International Tennis Federation [ITF]) as the index

to be used to evaluate the thermal comfort during the

sports activities. It is important to remember that this

empirical index is computed from the reading of the

dry-bulb temperature and two derived measures: the

natural wet-bulb temperature and the black-globe

temperature.

Moreover the same Authors, based on previous

researches, denoted that incorporating newly

available bioclimatic indices such as PMV instead of

WBGT would considerably improve sport-specific

heat stress modeling and current guidelines.

The main goal of this paper is to present an

innovative methodology to evaluate the thermal

comfort of the athletes considering PET and PMV

indices for cycling sport. The analysis will be carried

out for the Rio de Janeiro area considering the two

venues for the cycling sport and for the two

disciplines (Time Trial and Road Race).

This analysis will be developed considering the

men’s races. The developed statistical analysis will

demonstrate how it is possible to characterize the

thermal conditions of an athlete involved in a race.

Finally this analysis can be used to develop the

strategy’s assessment of the race.

2 MATERIAL AND METHODS

2.1 Research Design

The research is developed analyzing:

 The geographical data of the race area with a

particular focus on the tracks. For this analysis

Google Earth is used as Open Access map

system, as well as the free information available

on Internet;

 The meteorological data (wind direction, wind

speed, air temperature, relative humidity, cloud

coverage). This computer supported analysis has

been performed using the WindRose PRO3

software (Enviroware, 2015);

 The PET and the PMV thermal comfort indices.

This part of research is also computer-supported

through the RayMan software (Matzarakis et al.

2007, 2010).

2.2 Material

2.2.1 Geographical Data

To analyze the geographical data, the first step is

searching the tracks that will be used for the two

disciplines (Time Trial and Road Race) during Rio

de Janeiro 2016 Olympic Games.

This information is provided by Union Cycliste

International – International Cycling Union (UCI,

2015). In the UCI web-page it is possible to find the

tracks for the two disciplines.

Then the tracks are georeferenced using Google

Earth as Open Access map system (Figure 1).

2.2.2 Meteorological Data

The meteorological variables, needed for the

analysis described in this study, are wind direction,

wind speed, air temperature and relative humidity.

The meteorological observations at surface have

been obtained from the Jacarepagua and Santos

Dumont weather stations, whose locations are shown

in Figure 1. The distance between the two stations is

about 22 km.

Weather data have been collected for the time

period 1994-2014 (20 years). The meteorological

data have been analysed filtering out all the values

that were not measured in August, because the

Olympic Games will be held in Rio de Janeiro

between 5

and 21

August 2016.

Figure 1: Positions of the two meteorological stations. In

the red box the zone of competence for the road races is

indicated.

2.2.3 The WindRose PRO3 Software

A wind rose is a chart which gives a view of how

wind speed and wind direction are distributed at a

particular location over a specific period of time.

This representation allows summarizing in a single

plot a large quantity of data; therefore it is a very

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282

useful tool.

The wind roses presented in this work have been

produced with the WindRose PRO3 software

(Enviroware, 2015).

A time filter option allows analysing the wind

data and produce wind roses only for particular

years, months, days of the week or hours of the day.

It is also possible to produce wind roses only for day

or night hours, which are determined by the software

itself starting from the geographical position and the

time zone of the meteorological station. Monthly,

hourly and three-hourly wind roses are automatically

created by the software.

The WindRose PRO3 software has been used in

many sectors: meteorology, architecture, air quality,

oceanography, veterinary medicine, veterinary

epidemiology, wind energy, climate, aquatic botany

and agriculture. It has also been used for the analysis

of sport performances (Pezzoli et al., 2013; Pezzoli

and Bellasio, 2014).

2.2.4 The RayMan Software

The RayMan software (Matzarakis et al. 2007, 2010)

is widely employed in bioclimatological studies

applied to tourism activities and sport practices.

Such software combines many heat transfer models

with the heat sensation perceived in the human body.

It generates universal scales of thermal sensation,

which have large application in the outdoor sports

like road cycling (Matzarakis et al. 1999;

Brandenburg et al., 2007; Pezzoli et al., 2012). The

input variables needed by the RayMan software are:

 Date, hour and location (longitude and latitude,

altitude and time zone);

 Environmental and meteorological data like air

temperature (°C), pressure (hPa), relative

humidity (%), wind speed (m/s) and cloud

covering (octas);

 Personal data about the subject (weight, height,

age and sex);

 The heat transfer resistance of the clothing,

according with UNI EN ISO 9920/2004 and

the internal heat production (W), consequential

to the physical activity of the subject.

The outputs of the model are the two

bioclimatological indices (PMV and PET) which

provide the thermal perception and the grade of

physiological stress, as reported in Table 1.

The PMV predicts the normalized value of the

thermal comfort of a large group of people exposed

to similar environmental conditions, while the PET

has detailed thermo-physiological basis taking into

account the energy balance of the human body in

relationship with climatic conditions.

Table 1: Thermal sensations according to PMV and PET

values.

PMV PET [°C]

Thermal

perception

Grade of

physiological

stress

< -3.5 < 4 Very cold

Extreme cold stress

-3.5 - -2.5 4 - 8 Cold Strong cold stress

-2.5 - -1.5 8 - 13 Cool

Moderate cold

stress

-1.5 - -0.5 13 - 18 Slightly cool

Slight cold stress

-0.5 – 0.5 18 - 23 Comfortable

No thermal stress

0.5 – 1.5 23 - 29

Slightly

warm

Slight heat stress

1.5 – 2.5 29 - 35 Warm

Moderate heat

stress

2.5 – 3.5 35 - 41 Hot

Strong heat stress

> 3.5 > 41 Very hot

Extreme heat stress

2.3 Methods

2.3.1 The Evaluation of Meteorological

Conditions for Cycling Sport

As well described by Pezzoli et al. (2012) the

cycling sport is strongly influenced by the

meteorological variables. The wind direction, as

well as the wind speed, strongly influences the

performance in the cycling sport.

A correct climatological analysis, taking into

account this meteorological variable (wind), can be

fruitfully used by the coaches and the athletes to:

 Decide the training program (physical and

mental);

 Decide about the training site;

 Decide about the nutrition planning;

 Develop the material.

For what concerns the analysis of the wind direction,

it is decided to analyse the “True Wind Direction”

(TWD) failing to take into account the apparent

wind generated by the speed of the bicycle. The

TWD is measured in degrees considering the

Geographical North. The wind roses (Section 3.2)

are drawn considering a wind direction range of 30°.

Of course it is evident that also the air

temperature and the relative humidity influence the

performance in the cycling sport. In fact, as

mentioned before, the thermal comfort indices are

function of these two meteorological variables.

The typical day of each meteorological variable

has been evaluated by using the WindRose PRO3

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283

software. The hourly average wind direction, hourly

average wind speed, hourly average air temperature

and hourly average relative humidity as well as the

hourly standard deviation for all of these

meteorological variables are calculated in the typical

day.

Finally the rain, evaluated in term of cloud

coverage, is analysed and used as input in the

RayMan model for the evaluation of the PET and

PMV thermal indices.

2.3.2 The Evaluation of Thermal Comfort

Conditions for Cycling Sport

The analysis of the thermal comfort was carried out

considering the men’s category.

The thermal comfort indices (PET and PMV) are

evaluated for a target of athletes that represents an

average professional “climbing and trialist” cyclist’s

categories (age: 27, height: 1,75m, weight: 65kg as

suggested by Lucia et al., 2000).

It was decided to calculate the thermal comfort

indices for each hour for a time interval included

between 09.00LT ÷ 16.00LT. The input, for what

concerns the meteorological variables, are the

average of the meteorological variables corrected

using the standard deviation.

Moreover the indices are calculated for two

different conditions: restore and effort period. The

internal heat production (W) is considered equal to

80W for the restore period and equal to 300W for

the effort period (Pezzoli et al., 2012).

The heat transfer resistance of the clothing is

considered equal to 0.6clo (corresponding to a light

gym suit with a t-shirt) for the restore period and

equal to 0.3clo (corresponding to a t-shirt and short

pants) for the effort period.

3 RESULTS AND DISCUSSION

3.1 Analysis of the Venues for Cycling

Sports in Rio de Janeiro 2016

Olympic Games

The venues for cycling sports are localized in two

areas of Rio de Janeiro named Barra (Time Trial) and

Copacabana (Road Race) as illustrated in Figure 2.

A more detailed geographical representation of

the two different circuits is provided by UCI. Figure

3 illustrates the circuit of the Time Trial, for a total

length of 54.5 km, while Figure 4 represents the

circuit of the Road Race, for a total length of 241.5

km.

Figure 2: Location of the two areas for cycling sports in

Rio de Janeiro (courtesy: Rio 2016 Organising

Committee).

Comparing Figure 3 and Figure 4 with Figure 1 it is

possible to observe that the selected weather stations

are representative of both the circuits. Specifically

the weather station of Santos Dumont is the

reference for Copacabana area and the weather

station of Jacarepagua is representative for Barra

area.

It is also evident how the Time Trial race will be

carried out in Barra region, while the Road Race will

be held both in Copacabana (start and arrival) and in

Barra region.

Figure 3: Time Trial circuit (courtesy: UCI).

Figure 4: Road Race circuit (courtesy: UCI).

3.2 Analysis of Meteorological

Conditions in Rio de Janeiro in

August

The wind roses are shown in Figure 5a, 5b, 5c, 5d

and Figure 6a, 6b, 6c, 6d, respectively for the

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stations Jacarepagua and Santos Dumont. For each

station the wind roses have been produced for the

period 5-21 August and for four time intervals of the

day: 09.00LT ÷ 11.00LT, 12.00LT ÷ 14.00LT,

15.00LT ÷ 17.00LT and 18.00LT ÷ 20.00LT.

At the Jacarepagua station the prevailing wind

comes from the north eastern sector in the time

interval 09.00LT ÷ 11.00LT, from the southern

sector in the time periods 12.00LT ÷ 14.00LT and

15.00LT ÷ 17.00LT, and from the south western

sector in the time interval 18.00LT ÷ 20.00LT. In all

the time intervals wind speed from 1m/s to 3m/s

interests about 40% of the observations, while wind

speed greater than 5m/s interests about 5% ÷ 7% of

the observations, with the exception of the time

period 18.00LT ÷ 20.00LT where it is 2.3%. This

last time interval is also characterized by a high

value of calms (43%).

At the Santos Dumont station the prevailing

wind comes from the northern sector in the time

interval 09.00LT ÷ 11.00LT, and from the southern

sector in the remaining time intervals.

In the first time interval wind speeds from 1m/s

to 3m/s interest about 44% of the observations, in

the second and fourth time intervals they interest

about 25% of the observations, while in the third

time interval they interest about the 10% of the

observations. The third time interval is also

characterized by the higher percentage of wind

speeds greater than 5m/s (more than 30%) and by

the lower presence of calms (3.5%).

Considering the positions of the weather stations

(Figure 1), the pattern described by the wind roses is

typical of the breeze regimes, with wind blowing

from land to sea in the first hours of the morning,

and in the opposite direction during the afternoon.

Figure 5a: Wind roses of the Jacarepagua station. Time

interval: 09.00LT ÷ 11.00LT.

Figure 5b: Wind roses of the Jacarepagua station. Time

interval: 12.00LT ÷ 14.00LT.

Figure 5c: Wind roses of the Jacarepagua station. Time

interval: 15.00LT ÷ 17.00LT.

Figure 5d: Wind roses of the Jacarepagua station. Time

interval: 18.00LT ÷ 20.00LT.

Analysis of Thermal Comfort for Cycling Sport: A Case Study for Rio de Janeiro Olympic Games

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Figure 6a: Wind roses of the Santos Dumont station. Time

interval: 09.00LT ÷ 11.00LT.

Figure 6b: Wind roses of the Santos Dumont station. Time

interval: 12.00LT ÷ 14.00LT.

3.3 Analysis of Thermal Comfort in

Rio de Janeiro in August for the

Athletes of Cycling Sports

To analyze the thermal comfort in Rio de Janeiro the

two tables, presented by Blazejczyk et al. (2012) and

Brocherie and Millet (2015), are the reference.

These tables show the heat-stress indices’

temperature limits in reference to thermal sensation,

alert description and recommended sporting activity.

Table 2 summarizes the above mentioned tables.

Figure 7 and Figure 8 illustrate the PET and PMV in

the restore period for Copacabana and Barra areas

(Section 2.3.2).

Observing Figure 7 and Figure 8, it is possible to

note that around 12.00LT the thermal indices reach

high values (PET = 27 ÷ 31°C ; PMV = 1.1 ÷ 1.7)

for both the areas. It is also important to note that in

Copacabana the values of the thermal comfort

indices are lower than those obtained in the Barra

area.

Figure 6c: Wind roses of the Santos Dumont station. Time

interval: 15.00LT ÷ 17.00LT.

Figure 6d: Wind roses of the Santos Dumont station. Time

interval: 18.00LT ÷ 20.00LT.

Figure 7: PET and PMV thermal indices in the restore

period for Rio de Janeiro Copacabana area.

The maximum values of PET and PMV observed in

Figure 7 and Figure 8 correspond to a warm thermal

sensation and an alert description, as recommended

for sporting activity for WBGT, equal to “caution”.

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Table 2: Selected heat—stress indices’, temperature limits [°C] in reference to thermal sensations, alert description and

recommended sporting activity. Modification of the tables of Blazejczyk et al. (2012) and of Brocherie and Millet (2015).

Thermal

sensation

Alert description

Reccomended sporting activity

Index

WBGT[°C] PET [°C] PMV UTCI[°C]

Neutral Generally safe Unlimited/normal activity

<18 18 ÷ 23 -0.5 ÷ 0.5 9 ÷ 26

Warm Caution Increase exercise-to-rest ratio. Decrease

intensity and total duration of activity

18 ÷ 24

23 ÷ 35 0.5 ÷ 2.5 26 ÷ 32

Hot Extreme caution Activity of unfit, unacclimatized, high-

risk

b,c

subjects should be curtailed

24 ÷ 28 35 ÷ 41 2.5 ÷ 3.5 32 ÷ 38

Very hot Danger Activity for all except well acclimatized

should be stopped

28 ÷ 30 >41 >3.5 38 ÷ 46

Sweltering Extreme danger Cancel or stop all practice and

competition

>30

>46

Alert description/recommended sport activity for WBGT

While wearing shorts, t-shirt, ankle socks and sneakers

Internal heat production exceeds heat loss and core body temperature rises continuously without a plateau

Threshold (WBGT = 21°C) recommended by marathon organization in northern latitutdes

Threshold (WBGT > 30°C) recommended by most sporting governing bodies (i.e.: American College of Sport Medicine

[ACSM], International Tennis Federation [ITF], Women’s Tennis Association [WTA] and Fédération Internationale de Football

Association [FIFA])

Figure 8: PET and PMV thermal indices in the restore

period for Rio de Janeiro Barra area.

Figure 9: PET and PMV thermal indices in the effort

period for Rio de Janeiro Copacabana area.

In the early morning, as well as in the afternoon,

the indices show a comfortable situation from a

thermal comfort point of view.

Figure 10: PET and PMV thermal indices in the effort

period for Rio de Janeiro Barra area.

The values obtained in this analysis show that, in

the restore period, the clothing suites are to be

changed during the day moving from light gym suit

with a t-shirt to t-shirt and short pants.

Finally, the PET and the PMV values in the

effort period for Copacabana and Barra areas

(Section 2.3.2) are shown in Figure 9 and Figure 10.

Also for the effort period, the maximum values

of the PET and the PMV are confirmed between

12.00LT ÷ 13.00LT (PET = 27 ÷ 30°C; PMV = 3.2

÷ 3.7).

It is possible to note as the PET values during the

effort period are similar to the PET values during the

restore period. These results are function of a correct

choice of clothing that the athletes have to use

during the race and the restore period (Section

2.3.2).

Analysis of Thermal Comfort for Cycling Sport: A Case Study for Rio de Janeiro Olympic Games

287

However the PMV values in the effort period are

higher than the PMV values of the restore period.

Generally it is possible to observe as the maximum

values of the PET and PMV indices correspond to a

“caution – extreme caution” alert description

recommended for sporting activity for WBGT.

The same recommendations show that, in these

conditions, it is important to increase the exercise-

to-rest ratio as well as to decrease the intensity and

the total duration of activity. In the same time it is

very important that the athletes are well acclimatized

and that they prepare a correct plan and strategy for

nutrition and hydration (pre-event, event, post-

event).

4 CONCLUSIONS

The analysis of the thermal comfort of the athletes

during the next Rio de Janeiro Olympic Games,

made with an innovative methodology, is presented

in this research. The calculations have been carried

out for the men's category of the cycling sport. The

meteorological data of a 20-year long period have

been collected for two monitoring stations that are

representative for the race areas (Time Trial and

Road Race). The data of the months of August have

been analyzed in order to create the wind roses and

the typical days of the main variables. Two thermal

comfort indices (PET and PMV) have then been

calculated considering also the clothing type and the

power generated during the exercise. They have

been determined for the time period 09-16 LT and

for the resting and effort phases of both races.

It is important to note how the presented

methodology can be generalized to other sport as

well as to other venues. In fact the presented

RayMan model takes into account the personal data

about the subject (weight, height, age and sex) as

well as the internal heat production (W)

consequential to her/his physical activity.

Then it will be possible to change these reference

data to adapt the methodology and the model to the

analysed sport.

Finally, in the future, it will be interesting to

quantify the thermal comfort of the athletes

measuring directly the skin’s temperature and the

skin’s humidity of the athletes (Pezzoli et al., 2012).

This innovation in the research will help to quantify

correctly the thermal comfort and to improve the

alert description and the recommended sporting

activity (Table 2).

For these reasons, the procedure described in this

study gives useful information about the most

suitable clothing type for affording the race. The

results are also useful for defining pre, during and

post-race nutrition and hydration plans.

REFERENCES

Blazejczyk, K., Epstein, Y., Jendritzky, G., Staiger, H.,

Tinz, B., 2012. Comparison of UTCI to selected

thermal indices. Int. J. Biometeorol., 56:515-535.

Brandenburg, C., Matzarakis, A., Arnberger, A., 2007.

Weather and cycling – a first approach to the effects of

weather conditions on cycling. Meteorological

Applications, 14:61-67.

Brocherie, F., Girard, O., Millet, G.P., 2015. Emerging

environmental and weather challenges in outdoor

sports. In Climate – Special Issue “Climate Impacts on

Health”, Pezzoli, A., Editor. MDPI: Basel,

Switzerland, 3:492-521.

Brocherie, F., Girard, O., Pezzoli, A., Millet, G.P., 2014.

Outdoor exercise performance in ambient heat: time to

overcome challenging factors? Int. J. Hyperthermia,

30(8):547-549.

Brocherie, F., Millet, G.P., 2015. Is the Wet-Bulbe Globe

Temperature (WBGT) Index relevant for exercise in

the heat? Sports Med., DOI 10.1007/s40279-015-

0386-8.

Brode, P., Fiala, D., Blazejczyk, K., Holmer, I.,

Jendritzky, G., Kampmann, B., Tinz, B., Havenith, G.,

2012. Deriving the operational procedure for the

Universal Thermal Climate Index (UTCI). Int. J.

Biometeorol., 56:481-494.

Enviroware, 2015. Available online: http://www.enviro

ware.com/portfolio/windrose-pro3/ (accessed on 13

September 2015).

Lucia, A., Joyos, H., Chicarro, J.L., 2000. Physiological

response to professional road cycling: climber vs. time

trialist. Int. J. Sports Med., 21-7:505-512.

Jendritsky, G., Maarouf, G., Fiala, D., Staiger, H., 2002.

An up-date on the development of a universal thermal

climate index. In Proceedings of the 15

Conference

on Biometeorology/Aerobiology and 16

International

Congress of Biometeorology, Kansas City, MO, USA,

27 October – 1 November 2002.

Matzarakis, A., Mayer, H., Iziomon, M.G., 1999.

Application of a universal thermal index:

physiological equivalent temperature. Int J.

Biometeorol., 43:76-84.

Matzarakis, A., Rutz, F., Mayer, H., 2007. Modelling

Radiation fluxes in simple and complex environments

– Application of the RayMan model. Int J

Biometeorol., 51:323-334.

Matzarakis, A., Rutz, F., Mayer, H., 2010. Modelling

Radiation fluxes in simple and complex environments:

basics of the RayMan model. Int J Biometeorol.,

54:131-139.

Pezzoli, A., Baldacci, A., Cama, A., Faina, M., Dalla

Vedova, D., Besi, M., Vercelli, G., Boscolo, A.,

Moncalero, M., Cristofori, E., Dalessandro,, M.,

WPPDSports 2015 - Special Session/Symposium on Weather, Position and Performance data in Outdoor Sports

288

2013. Wind-wave interactions in enclosed basins: The

impact on the sport of rowing. In Sport Physics,

Clanet, C., Editor. Ecole Polytechnique de Paris: Paris,

France, 139–151.

Pezzoli, A., Bellasio, R., 2014. Analysis of Wind Data for

Sports Performance Design: A Case Study for Sailing

Sports. Sports. 2(4):99-130.

Pezzoli, A., Cristofori, E., Gozzini, B., Marchisio, M.,

Padoan J., 2012. Analysis of the thermal comfort in

cycling athletes. Procedia Engineering, 34:433-438.

Pezzoli, A., Cristofori, E., Moncalero, M., Giacometto, F.,

Boscolo, A., Bellasio, R., Padoan, J., 2015. Effect of

the environment on the sport performance: computer

supported training – A case study for the cycling

sports. In Sport Science Research and Technology

Support, Cabri, J., Pezarat Correia, P., Barreiros, J.,

Editors. Springer: London, UK, 1-16.

Rio de Janeiro Olympic Games Organizing Committee.

Available on-line: http://www.rio2016.com/mapa-de-

instalacoes (accessed on 20 September 2015).

UCI, 2015. Available on-line: http://www.uci.ch/

road/ucievents/2016-road-olympic-games/196852016/

(accessed on 19 September 2015).

Analysis of Thermal Comfort for Cycling Sport: A Case Study for Rio de Janeiro Olympic Games

289