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Energy consumption in buildings and female thermal demand

Energy consumption in buildings and female
thermal demand
Boris Kingma*and Wouter van Marken Lichtenbelt
Energy consumption of residential buildings and oces adds
up to about 30% of total carbon dioxide emissions; and
occupant behaviour contributes to 80% of the variation in
energy consumption1. Indoor climate regulations are based
on an empirical thermal comfort model that was developed
in the 1960s (ref. 2). Standard values for one of its primary
variables—metabolic rate—are based on an average male,
and may overestimate female metabolic rate by up to 35%
(ref. 3). This may cause buildings to be intrinsically non-
energy-ecient in providing comfort to females. Therefore, we
make a case to use actual metabolic rates. Moreover, with a
biophysical analysis we illustrate the eect of miscalculating
metabolic rate on female thermal demand. The approach
is fundamentally dierent from current empirical thermal
comfort models and builds up predictions from the physical and
physiological constraints, rather than statistical association to
thermal comfort. It provides a substantiation of the thermal
comfort standard on the population level and adds flexibility
to predict thermal demand of subpopulations and individuals.
Ultimately, an accuraterepresentation of thermal demand of all
occupants leads to actual energy consumption predictions and
real energy savings of buildings that are designed and operated
by the buildings services community.
As the built environment is focusing more on design of energy-
efficient buildings (for example, near-zero-energy buildings), we
argue that indoor climate standards should accurately represent
the thermal demand of all occupants. Otherwise there is a great
risk that occupants will adapt their behaviour to optimize personal
comfort, which may in turn nullify the effects of supposed
energy-efficient designs. Furthermore, various fields in commerce,
science and policymaking depend on accurate predictions of
building energy consumption. For instance, commercial incentives
for building renovations premised on energy-saving predictions;
scientific climate change simulations require building energy
consumption predictions to account for warming effects in winter4;
and policymaking for resource management requires integrated
resource assessments including energy consumption by buildings5.
The total variation in building energy consumption that is
explained by occupant behaviour includes operating the thermostat,
windows or air conditioning system1. In general, females prefer a
higher room temperature than males in home and office situations,
and mean values may differ as much as 3 K (males: 22 C versus
females: 25 C; refs 6,7). Despite this discrepancy in preferred room
temperature, no significant gender effect is found with respect to
the mean skin temperature range that is associated with thermal
comfort (males: 32.8–33.8 C versus females: 32.4–33.6 C; ref. 8).
Indoor thermal environment design is primarily based on
PMV/PPD (predicted mean vote/percentage people dissatisfied)
criteria. The PMV is expressed on the ASHRAE 7-point Thermal
Sensation Scale ranging from cold (3) to hot (+3). This vote
is linked to thermal discomfort through the PPD (ref. 9). Two
main input variables for the model are metabolic rate and
clothing insulation; however, the accuracy of these variables is
in general poorly defined10,11. Nevertheless, standard reference
values for the metabolic rate and clothing are tabulated and
used worldwide2,12,13. With respect to the metabolic rate, the
metabolic equivalent (MET) is used to express the metabolic
cost of an activity relative to the resting metabolic rate, and its
value (1 MET =4.186 kJ kg1h158 W m2) is set by convention
based on the resting metabolic rate of only one 70kg, 40-year-old
male3. This may have significant consequences because 58 W m2
may overestimate resting heat production of women up to
35% (ref. 3). Similarly, with increasing age, basal metabolic
rate decreases14. Thus, current indoor climate standards may
intrinsically misrepresent thermal demand of the female and senior
subpopulations10,15. The PMV/PPD model uses the metabolic rate to
calculate the environmental conditions that satisfy thermal balance
between the body and the environment (see Fig. 1, right part: skin
to environment). However, from a biophysical perspective, thermal
balance within the body has to be satisfied as well (see Fig. 1).
Thermal balance within the body is dictated by both metabolism
and the composite thermal insulation provided by tissues (that
is, body composition and skin blood flow). The influence of
thermal insulation is especially relevant in the case of lean versus
obese. The larger insulation provided by adipose tissue results in
greater core-to-skin temperature gradient and a lower mean skin
temperature for obese compared with lean16. Consequently, these
physiological characteristics co-determine the thermal demand
from the environment. The PMV/PPD model was published in the
1970s and at that time biophysical models that incorporate the
influence of tissue insulation were not widely used. However, since
that time several biophysical models of human thermal balance have
been developed17–19. Therefore, the knowledge gained from these
models could be used to enhance the PMV/PPD model.
It has been suggested that thermal balance within the ther-
moneutral zone is a prerequisite of steady-state thermal comfort20.
The thermoneutral zone is defined in physiological terms as the
range of operative temperatures where an organism can maintain its
body temperature without regulatory changes in metabolic rate (for
example, shivering or non-shivering thermogenesis) or sweating21
(see Fig. 2). In relation to thermal comfort this means that opera-
tive temperatures that are thermally comfortable (thermal comfort
zone) coincide with, or at least form a subset of, the temperatures
where the body requires no regulatory metabolic heat production or
sweating to maintain thermal balance (thermoneutral zone)20,22. The
exact positioning of the thermoneutral zone may thus change with
activity, body composition (tissue insulation) and clothing level.
In this study we investigate the thermal state of young adult
females performing light office work and we use a biophysical
modelling approach to test whether these thermal states fall within
Department of Human Biology, NUTRIM School of Nutrition and Translational Research in Metabolism of Maastricht University Medical Center+,
PO Box 616, 6200 MD Maastricht, The Netherlands. *e-mail:
Core temperature
Metabolic heat
Heat loss
Air temperatureSkin temperature
Tissue insulation Clothing insulation
Body fat mass, muscle
mass and skin blood flow
influence tissue insulation
Body EnvironmentSkin
Conduction, convection Conduction, convection, radiation, evaporation
Figure 1 | Schematic view of human heat balance. Heat balance from core to skin (within body) and from skin to air (between body and the environment).
The open arrows denote heat flow within the body via conduction through tissues and convection through blood flow; and between the body and
environment via conduction, convection, radiation and evaporation. Body tissue insulation provides resistance to metabolic heat within the body and
determines the temperature gradient between core and skin. Likewise, clothing also provides resistance to body heat loss and co-determines the
temperature gradient between skin and air.
their thermoneutral zone (see Methods and Supplementary Table).
With this analysis we aim to point out the importance of using the
actual metabolic rate, instead of a standard one based only on a male.
Therefore, the biophysical model may provide a constructive way
forward from the empirical thermal comfort standard.
The measured group average metabolic rate for young adult
females while performing light office work is 48 ±2 W m2, which is
significantly lower (p<0.01) than the ASHRAE standard values for
metabolic heat production associated with this activity (from resting
seated: 60 W m2or 20% overestimation, to seated filing: 70 W m2
or 32% overestimation). The biophysical analyses using both the
measured and range of reference values for metabolic rate is shown
in Fig. 3 (see Methods for details on how this Figure is constructed).
The grey areas in Fig. 3 indicate the thermoneutral zones; that is,
they depict the area where heat loss equals measured metabolic
heat production. Open circles indicate actually measured mean skin
temperature and operative temperature baseline recordings. When
using the measured metabolic rate (Fig. 3, right area), measurements
are located inside the thermoneutral zone. This is in great contrast to
where all model parameters are kept equal except for the metabolic
rate for which the standard reference values for light office work are
used (Fig. 3, left area).
This biophysical analysis shows that mean skin temperature and
thermal environment of young adult females performing light office
work falls within their thermoneutral zone, but only if the correct
(actual) metabolic rate is used. Furthermore, we confirm that the
metabolic rate of young adult females performing light office work
is significantly lower than the standard values for the same type
of activity. With these results we argue that the current metabolic
standards should be adjusted by including the actual values for
females to reduce gender-discriminating bias in thermal comfort
predictions, and consequently, to reduce prediction bias in building
energy consumption.
The body senses its thermal state through temperature-sensitive
receptors in core and skin tissues20. Various studies have examined
skin temperatures that are associated with thermal comfort,
and estimates range from wide (31.5 Ts35.5 C) to more
conservative (32.4 Ts33.6 C) values8,23. The former seems to
coincide with the entire thermoneutral zone of young adult females
performing light office work (see 31.5Ts35.5 C, Fig. 3), whereas
the latter comprises only a subset of the thermoneutral zone (see
32.4 Ts33.6 C, Fig. 3). This discrepancy between studies may
in part have been caused by differing number of skin sites that
have been measured. In general, more skin sites yields more reliable
results. Using a standard that consists of less than 10 skin sites
leads to significantly lower reliability24. On top of that, within limits
imposed by physics and physiology, human psychological factors
(for example, thermal adaptation due to geography) may also play a
role in what skin temperatures are considered comfortable25.
Constraining the model results further to skin temperatures that
are associated with thermal comfort it is possible to identify a
biophysical thermal comfort zone22. For the given conditions, the
biophysical thermal comfort zone for females ranges from 23.2 to
26.1 C (for mean skin temperature ranging 32.4Ts33.6 C).
As introduced, we make a case to use more reliable values
for female metabolic rate in thermal comfort prediction. Future
technological advances may yield devices that accurately measure
individual metabolic rate (for example, via smart watches and
so on). Until that time, one way to go forward may be by using
resting metabolic rate equations that take into account the effects
of age, sex and body size (for example, revised Harris and Benedict
equations for resting metabolic rate26). The resting metabolic rate
can be converted from watt to watt per square metre by using the
appropriate equation for body surface area (for example, ref. 27).
Furthermore, the resting metabolic rate can also be scaled to the
activity type using the MET scaling factors.
The use of more accurate metabolic rates implies that the
PMV/PPD model requires recalibration. The reason for this is in
the very nature of the PMV/PPD model: it is an empirical model
and it has been fitted against thermal sensation votes using the
standardized values for metabolic rate. In the long run, recalibration
to any unforeseen subpopulation is not a sustainable strategy to
maintain. It has been suggested that a better method to improve
the PMV/PPD model is to revise its physiological construction15,28.
This in turn makes it possible to fundamentally understand and
take into practice the effects of group and individual differences
Metabolic rate
Operative temperature
Skin temperature
Operative temperature
Lower critical
Upper critical
temperature Lower critical
Upper critical
Thermoneutral zone Thermoneutral zone
Shivering Sweating
Figure 2 | Two methods to depict the thermoneutral zone. a, The classical
method indicating the dependence of metabolic rate versus operative
temperature. b, The method used in this paper describing the relation
between skin temperature versus operative temperature. The range to the
left of the thermoneutral zone depicted with ‘shivering’ indicates that more
heat production is required to maintain thermal balance, and the range to
the right depicted by ‘sweating’ indicates that more heat loss is required to
maintain thermal balance. Within the open bounds it is possible for the
body to maintain core temperature.
14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Operative temperature (°C)
Mean skin temperature (°C)
Thermoneutral zone,
measured metabolic rate
Measured thermal state of
young adult females
performing light oce work
Thermoneutral zone,
standard metabolic rate
Figure 3 | The steady-state thermoneutral zone (grey areas) and baseline
measurements (open circles). The bottom of the thermoneutral zone is
associated with maximal tissue insulation, and vice versa for the top. Left
area: thermoneutral zone using the standard value for metabolic rate
associated with light oce work (ranging from 60 to 70W m2). Right
area: thermoneutral zone using measured metabolic rate of females
performing light oce work.
in physiological characteristics such as lean versus obese, or the
consequences on preferred thermal environment of changes in
physiology (for example, ageing, acclimatization or illness).
The biophysical approach in this study is an essential step towards
such a revision. In our opinion it allows for a significant improve-
ment of the empirical model because of the physiological construc-
tion that includes the constraint for thermal balance within the body.
To do so, it is crucial to take into account not only the metabolic
rate but also the physiological range of body tissue insulation, which
may vary with body composition, gender and age, but also between
individuals. Thus, the biophysical model provides insight into ther-
mal comfort boundaries for subpopulations such as females, males,
children and seniors. These should be addressed in future studies
that measure subjective thermal comfort as well as physiological
characteristics such as metabolic rate and tissue insulation. The
biophysical approach provides a fundamental substantiation of the
PMV/PPD model on the population level and adds flexibility to
predict thermal comfort of subpopulations or individuals. Another
issue that deserves attention is thermal behaviour. How do physio-
logical characteristics relate to behaviour, and to what extent does a
deviation from the thermoneutral zone trigger an action?
The main points here are that thermal comfort models need
to adjust the current metabolic standard by including the actual
values for females. Consequently, thermal comfort models need
either to be recalibrated or enhanced using a biophysical approach
as presented here. This in turn will allow for better predictions
of building energy consumption, by reducing the bias on thermal
comfort of subpopulations and individuals.
Methods and any associated references are available in the online
version of the paper.
Received 20 May 2015; accepted 30 June 2015;
published online 3 August 2015
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The authors would like to express their gratitude to C. Jacquot and L. Schellen for
performing measurements, and A. Frijns for fruitful discussions. This study was
supported by grants from AgentschapNL (INTEWON: EOSLT10033) and TKI Energo
and TKI Solar Energy (TRECO: TEGB|13023).
Author contributions
B.K. contributed to experimental work, project planning, data analysis, biophysical
modelling, and manuscript writing. W.v.M.L. contributed to project planning, data
analysis, manuscript writing and project funding.
Additional information
Supplementary information is available in the online version of the paper. Reprints and
permissions information is available online at
Correspondence and requests for materials should be addressed to B.K.
Competing financial interests
The authors declare no competing financial interests.
The thermoneutral zone. The thermoneutral zone is classically depicted as
described in ref. 29: metabolic rate versus operative temperature and bound by the
lower critical temperature and the upper critical temperature (see Fig. 2a). From
the perspective of thermal balance, thermoneutral operative temperatures near the
lower critical temperature correspond to relatively low skin temperatures, and vice
versa for thermoneutral operative temperatures near the upper critical
temperature. This leads to a new method to depict the thermoneutral zone, which
is used in the remainder of this paper (see Fig. 2b). The open range to the left of the
thermoneutral zone depicted with ‘shivering’ indicates that more heat production is
required to maintain thermal balance, and the open range to the right depicted by
‘sweating’ indicates that more heat loss is required to maintain thermal balance.
Note that depending on mean skin temperature there is overlap between
thermoneutral operative temperatures, and operative temperatures that require
extra heat production or extra heat loss. Thermal balance in the thermoneutral
zone is always a constellation of skin temperature and operative temperature.
Therefore, it may be inadequate to define a thermal comfort zone only by
operative temperature.
The exact skin temperature range of the thermoneutral zone is bounded by the
metabolic rate and the capacity of the body to regulate tissue insulation22. The body
regulates tissue insulation by constricting and dilating blood vessels in skin tissue.
To preserve body heat the body constricts blood vessels (that is, vasoconstriction),
which results in maximal tissue insulation and minimal skin temperatures. To
enhance body heat dissipation the body dilates blood vessels (that is, vasodilation),
which results in minimal tissue insulation and maximal skin temperatures30.
Biophysical analysis. For the biophysical analysis a model is used that describes
the relation between body core temperature, skin temperature and operative
temperature (see Fig. 1)22. The model is used to determine core temperature for a
range of mean skin temperatures (28–38C) and operative temperatures
(14–32 C), whilst satisfying thermal balance. Overall thermal balance is achieved
when the following conditions are met: (1) Metabolic heat production equals
internal body heat transport. (2) Metabolic heat production equals external body
heat loss. These conditions can be rewritten to an equivalent such that internal
body heat transport equals external body heat loss. Note that metabolic heat
production is then eliminated from the condition of thermal balance, yet still
determines the actual body heat transport and heat loss. The model details are
described in ref. 22. For the purpose of this paper the steps for constructing the
young adult female thermoneutral zone as depicted in Fig. 3 are given below:
Define body surface area (A), clothing insulation (Icl), relative humidity (ϕ)
skin wettedness, (w), wind speed (vair) and Lewis relation (λ).
A=1.88 m2
Icl =0.105 m2K W1(0.68 clo)
w=0.06 ()
vair =0.09 m s1
λ=2.2 C mmHg1
Define minimal and maximal metabolic rate (Mmin and Mmax) based on 99%
confidence interval of energy expenditure measurements and correct for
respiratory heat loss (that is, consider only heat transfer to and from skin surface;
assumed 8% of metabolic rate31).
Mmin =(10.08)×84 W=77 W
Mmax =(10.08)×97 W=89 W
Define minimal and maximal body tissue insulation (Ibody,min and Ibody,max), (skin +
fat layer 4 mm)30,32.
Ibody,min =0.031 m2K W1
Ibody,max =0.112 m2K W1
Define minimal and maximal body core temperature (Tc,min and Tc,max).
Tc,min =36.5 C
Tc,max =37.5 C
Calculate minimal and maximal skin temperature that support internal heat
balance (Ts,min and Ts,max) according to ref. 22:
Ts,min =Tc,min Mmax ×Ibody,max/A[C]
Ts,max =Tc,max Mmin ×Ibody,min/A[C]
Define 500 ×500 point grid for Tsand Ta
Tsbetween 28 and 38 C
Tabetween 14 and 32 C
For each point in the grid (Tsand Ta): Calculate combined convective (hc) and
radiative (hr) contribution to insulation provided by air (Ia) according to ref. 30:
hc=0.19×(100×vair )0.5 ×(298/(Ta+273.15)) [clo1]
Ia=0.155/(hc+hr)[m2K W1]
Calculate evaporative heat loss according to ref. 17:
Qe=w×λ×hc×(PsϕPair)×Fpcl [W m2]
Ps=γ×100exp(18.9654, 030/(Ts+235)) [Pa]
Pair =γ×100exp(18.9654, 030/(Ta+235)) [Pa]
γ=0.00750061683 [mmHg Pa1]
Fpcl =1/(1+0.143×(hc/0.155)×(Icl/0.155)) [−]
Calculate body tissue insulation according to ref. 22:
Ibody =Ibody,max +(TsTs,min)
×(Ibody,max Ibody,min)/(Ts,min Ts,max )[m2K W1]
where (Ibody,min Ibody Ibody,max)
Calculate Tcsatisfying internal and external heat balance according ref. 22:
Tc=(Ibody/0.92)×((TsTa)/(Icl +Ia)+Qe)+Ts[C]
Calculate external heat loss (Qout)
Qout =A×((TsTa)/(Icl +Ia)+Qe)[W]
Keep points for which Tcbetween Tc,min and Tc,max. Keep points for which Qout
between Mmin and Mmax and plot remaining points in Figure (Tsversus Ta).
The exact position of the thermoneutral zone depends on the metabolic rate,
body insulation and clothing level. Higher metabolic rate and/or clothing level
shifts the thermoneutral zone to lower operative temperature and higher body
insulation shifts the neutral zone to lower operative and mean skin temperature,
and vice versa for lower metabolic rate and/or clothing level and lower
tissue insulation.
Accuracy statement. The model in this paper combines the main principles that are
important to describe internal and external human thermal balance. Nevertheless,
it is a simplification of reality and may not always well-predict temperatures,
especially for non-steady-state conditions. Likewise, the model parameters
are obtained from elaborate experimental studies, but may include measurement
errors. Therefore, to obtain a conservative view of how the thermoneutral
zone is situated we used parameter ranges instead of set values for metabolic
rate, core temperature and body tissue insulation. All steady-state, comfortable
(32.4Ts33.6C) measurements fall within the computed thermoneutral
zone for these conditions (see Fig. 3). When including non-steady-state baseline
measurements and skin temperatures outside comfortable skin temperature
range, 14% of measurements are situated just outside the model prediction
(mean absolute distance from thermoneutral zone for these points is 0.3 K).
Measured data. The data for the analysis were obtained in the context of a larger
study performed in our laboratory on thermal preference in young adult females33.
During the study 16 young female participants were lightly clothed
(0.58 Clo +0.10 Clo provided by chair), sitting behind a desk and were
randomly exposed to room temperature protocols in a climate chamber. For the
purpose of this study only steady-state baseline data from these protocols are used.
Operative temperature and relative humidity are measured using
wireless sensors (iButton, DS1923, Maxim Integrated Products; accuracy
±0.1 C). Skin temperature is also measured with iButtons (DS1922L,
accuracy ±0.1 C) at the 14 positions as described by ISO 9886 standard33.
Energy expenditure of young females performing light office work is
measured by indirect calorimetry (Maastricht Instruments, accuracy ±5%).
Recordings of baseline CO2production and O2uptake are converted into their heat
equivalent using the Weir equation34. The ASHRAE listed values for seated light
office work range from ‘seated quiet’ (60 Wm2) to ‘seated filing’ (70 Wm2).
Measured metabolic rate is compared with the standard values using a one-sample
t-test with significance level α=0.05. Data are presented as mean ±s.e.m. Whole
body fat percentage is measured through dual X-ray absorptiometry (Hologic,
accuracy ±5%).
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and tropical mammals and birds in relation to body temperature, insulation,
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in resting and exercising men in cold water. J. Appl. Physiol. 52,
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protein metabolism. J. Physiol. 109, 1–9 (1949).
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... In the high-level temperature areas, the memory scores of females were higher than that of males, while in the low temperature areas, memory scores were not significantly different between the two genders. This is consistent with previous studies [16], which may be due to the fact that female generally prefer higher indoor temperatures than males [53,54]. ...
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... Often, people need to put on an additional layer of clothes if sitting at their desk for extended periods. This is especially common for women, as described in [4] and [5]. These studies find that females prefer higher room temperatures than males, based on large scale field surveys and actual metabolic rate through biophysical analysis. ...
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The smart control informed by IoT sensors and enabled by remotely controlled devices can optimize the building operation to minimize unnecessary energy consumption and improve indoor thermal comfort. This paper quantifies the potential for electricity savings in small office buildings from smart thermostat control and occupancy-informed smart plug control. This is done by simulating the effect of adaptive setpoint temperature, occupancy-based HVAC control, and night-purge free cooling on small office buildings across all major climate zones in the United States. Adopting these smart control measures can achieve 8.9% to 20.4% of savings in total electricity consumption of small office buildings, or equivalent to annual reductions between 12.2 kWh/m2 and 30.4 kWh/m2 in electricity usage intensity. Among all climate zones, the hot and dry climates benefit the most from proposed smart controls and achieve the highest percentages of electricity savings
... However, achieving consistent thermal comfort for all individuals in a shared environment is challenging, due to the variability of individual thermal physiology and preferences (Richard & Gail Schiller, 1998). As few as 11% buildings have 80% or more participants expressing satisfactory thermal comfort , which affects motivation and performance (Cui et al., 2013) and gender equality (Irfan, 2015;Kingma & Van Marken Lichtenbelt, 2015). ...
Thermal physiology and psychophysics are complex and nuanced, with significant variability between individuals. Wearable devices have the potential to offer customizable microclimate control. However, individual experiences with different supplemental heating strategies are likely to vary considerably in unconstrained environments. The physiological responses, psychophysical effects, and qualitative experiences of participants using five readily available heating strategies were collected in a quasi-field study environment ( n=17). Although all devices maintained or increased fingertip temperature, effects observed from controlled studies of thermal physiology are not clearly seen. Physiological, perceptual, and experiential data are presented, exploring heating technologies and thermal comfort in typical indoor environments.
... Les valeurs standards pour l'une de ses variables principales -l'activité métabolique-sont calculées sur un homme moyen, qui surévaluerait l'activité métabolique d'une femme jusqu'à 35%. (Kingma et van Marken Lichtenbelt 2015) Il s'agissait plus précisément d'un homme de 40 ans pesant 70kg (Byrne et al. 2005), ce qui aboutit au résultat que les femmes en tant que groupes sont moins souvent satisfaites des températures dans les bureaux, ayant soit plus froid soit plus chaud que leurs collègues masculins, et ayant généralement une préférence pour que la température soit augmentée (Karjalainen 2007 ;Van Hoof 2008). On imagine l'impact que la remise en question de ce type de standards peut avoir sur la recherche de baisse de consommation énergétique actuelle dans la réhabilitation ou la construction de nouveaux bâtiments. ...
Depuis les années 2010, les projets d'urbanisme français intégrant les enjeux d'inégalités de genre se multiplient, touchant principalement les espaces publics et la rénovation urbaine. Des pratiques et concepts féministes se diffusent auprès de professionnel·le·s peu acculturé·e·s au sujet.Par une démarche de recherche-action féministe constructiviste mêlant travail d'archives et observations de réseaux spécialisés ainsi que de projets à Paris et Villiers-le-Bel, cette thèse analyse l'évolution des pensées, normes et pratiques genrées, ou régimes de genre, des milieux de l'urbanisme. Utilisant l'arrivée des approches explicitement genrées comme révélatrice de normes jusqu'alors tacites, elle remet en question la "nouveauté" du lien entre genre et urbanisme et ce que sa légitimation actuelle révèle de l'urbanisme français et remet en question.Montrant que l'urbanisme est toujours genré, ce travail explore l'amnésie collective entretenue autour de l'héritage théorique et pratique féministe en urbanisme, remontant au moins jusqu'aux années 1970. Il interroge les facteurs de la montée en puissance contemporaine de ces idées et approches égalitaires : les contextes politiques et culturels des organisations où le sujet s'infuse; la féminisation professionnelle et le rôle d'une masse critique de personnes concernées (femmes, minorités LGBTIQ, féministes); la légitimation d'expert·e·s et leur travail en réseau. Enfin, une analyse à l'échelle des actrices et acteurs individuel·le·s est proposée pour comprendre comment concepts et pratiques genré·e·s sont adapté·e·s par les spécialistes du genre puis reçu·e·s et approprié·e·s (ou non) par les urbanistes non-spécialistes.
... Although this has been recognised for some time, it continues to be a problem. Research shows that basing a building's environmental requirements only on the male metabolic rate may mean they could be 'intrinsically non-energy-efficient in providing comfort to females' [30]. Thus, even within the human species, the idea of 'quality' is contested and environments privilege certain stakeholders and disadvantage others. ...
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The article explores how the quality of life within a deprived urban environment might be improved through the ‘gamification’ of and interaction with, more-than-human elements within the environment. It argues that such quality may be achieved through the community’s multicentered value from the bottom up. This is shown through the case study of the Co-De|GT urban mobile application that was developed in the Synergetic Landscapes unit through real-life research by design experimental studio teaching. Complimentary experimentation took place during the Relating Systems Thinking and Design 10 symposium in the Co-De|BP workshop, where experts were able to be collocated for interactive real-time data gathering. This application addresses the need for collective action towards more-than-human synergy across an urban ecosystem through gamification, community collaboration and DIY culture. It intends to generate a sustainable, scalable token economy where humans and non-humans play equal roles, earning, trading and being paid for goods and services to test such potentials for future economies underpinned by blockchain. This work diverges from dominant economic models that do not recognise the performance of and the limits to, material extraction from the ecosystem. The current economic model has led to the global financial crisis (GFC). Furthermore, it is based on the unsustainable perpetual consumption of services and goods, which may lead to the untangling and critical failure of the market system globally. Therefore, this work investigates how gamification and tokenization may support a complementary and parallel economic market that sustains and grows urban ecosystems. While the research does not speculate on policy implications, it posits how such markets may ameliorate some of the brittleness apparent in the global economic model. It demonstrates a systemic approach to urban ecosystem performance for the future post-Anthropocene communities and economies.
... Questões como: difi culdades com a temperatura ambiente (tipicamente banalizada nas organizações, como apontam Kingma & van Marken Lichtenbelt, 2015); trabalho de cuidado afetivo e de apoio operacional esperado das mulheres, invisibilizado nas organizações, mas que cria problemas na organização do trabalho, principalmente para o crescimento das mulheres (Dorna & Muniz, 2018); desenho de progressões funcionais e outras modalidades de reconhecimento que não considerem períodos como licença maternidade (Leal et al., 2017); cargos de chefi a cuja ocupação é inviável para uma mulher (Yannoulas, 2011); relações socioprofi ssionais marcadas por expectativas ambivalentes de docilidade e força, desde que não ameace o lugar da masculinidade (Molinier, 2004). Todas são exemplos de como há estruturas específi cas a serem contempladas nas clínicas, que são, geralmente, diluídas em outros aspectos mais "gerais" do contexto de trabalho. ...
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The indoor environment critically affects occupant health and comfort, especially since humans spend most of the day indoors. Meanwhile, occupant activities, preferences, and behaviors may contribute to a significant amount of building energy consumption. The focus of environmental buildings shifted from automated systems to a paradigm of collective environmental design since the second half of the 20th century, emphasizing human dimensions in building performance, which allows occupants to participate as active/passive actuators and sensors. Concurrently, increased environmental awareness further spurred the green building movement intending to encourage more high-performance buildings. The question remains as to whether high-performance buildings are also healthy buildings. This dissertation aims to cast new light on how environmental design and building systems work for people as well as how building sensors and human senses work together to inform the organization and optimization of various performance targets such as sustainability, public health, and resiliency. Special attention is given to the non-visual environment attempting to facilitate human-in-the-loop of the building design and operation processes. In order to achieve this goal, environmental monitoring, data analysis, and human subject recruitments are developed to characterize the human dimension of building performance.
In Spain the average temperature has increased by 1.7°C since pre-industrial times. There has been an increase in heat waves both in terms of frequency and intensity, with a clear impact in terms of population health. The effect of heat waves on daily mortality presents important territorial differences. Gender also affects these impacts, as a determinant that conditions social inequalities in health. There is evidence that women may be more susceptible to extreme heat than men, although there are relatively few studies that analyze differences in the vulnerability and adaptation to heat by sex. This could be related to physiological causes. On the other hand, one of the indicators used to measure vulnerability to heat in a population and its adaptation is the minimum mortality temperature (MMT) and its temporal evolution. The aim of this study was to analyze the values of MMT in men and women and its temporal evolution during the 1983-2018 period in Spain’s provinces. An ecological, longitudinal retrospective study was carried out of time series data, based on maximum daily temperature and daily mortality data corresponding to the study period. Using cubic and quadratic fits between daily mortality rates and the temperature, the minimum values of these functions were determined, which allowed for determining MMT values. Furthermore, we used an improved methodology that provided for the estimation of missing MMT values when polynomial fits were inexistent. This analysis was carried out for each year. Later, based on the annual values of MMT, a linear fit was carried out to determine the rate of evolution of MMT for men and for women at the province level. Average MMT for all of Spain’s provinces was 29.4 °C in the case of men and 28.7 °C in the case of women. The MMT for men was greater than that of women in 86 percent of the total provinces analyzed, which indicates greater vulnerability among women. In terms of the rate of variation in MMT during the period analyzed, that of men was 0.39 °C/decade, compared to 0.53 °C/decade for women, indicating greater adaptation to heat among women, compared to men. The differences found between men and women were statistically significant. At the province level, the results show great heterogeneity. Studies carried out at the local level are needed to provide knowledge about those factors that can explain these differences at the province level, and to allow for incorporating a gender perspective in the implementation of measures for adaptation to high temperatures
Despite many decades of research examining thermoregulatory responses under varying cold stresses in humans, very little is known about the variability in metabolic heat production and shivering activity. Here, we used a novel closed-loop mean skin temperature clamping technique with a liquid-conditioned suit to isolate the effects of mean skin temperature on the subjective evaluation of thermal sensation, heat production, shivering responses, and oxidative fuel selection in young, lean and healthy men (n = 12) and women (n = 12). Our results showed a skin temperature-dependent increase in metabolic heat production (5.2±1.0 kJ/min, 5.9±1.0 kJ/min and 7.0±1.0 kJ/min with skin temperature maintained at 31°C, 29°C and 27°C, respectively; P< 0.0001) and shivering intensity in both men and women (0.6±0.1 %MVC, 1.1±0.4 %MVC and 2.5±0.7 %MVC, respectively; P<0.0001), including sex-dependent differences in heat production at all three temperatures (P < 0.005). Even when controlling for lean body mass and fat mass, sex differences persisted (P = 0.048 and P = 0.004, respectively), whereas controlling for differences in body surface area eliminated these differences. Interestingly, there were no sex differences in the cold-induced change in thermogenesis. Despite clamping skin temperature, there was tremendous variability in the rate of heat production and shivering intensity. Collectively this data suggests that many of the inter-individual differences in thermogenesis and shivering may be explained by differences in morphology and body composition.
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A new model to evaluate individual thermal comfort using mean skin temperature was proposed. Twenty-two subjects’ local skin temperatures were measured in a sleeping posture at air temperatures of 21℃, 24℃, 26℃ and 29℃. Mean skin temperatures were calculated using a formula with 10 measuring locations on the skin. The thermal comfort levels and thermal sensation of the subjects were also investigated by questionnaire. Based on the experimental data, an evaluation model of an individual’s thermal comfort using mean skin temperature was developed using the Mahalanobis distance discrimination method. Seventy two per cent of the total subjects’ thermal comfort levels was correctly evaluated using this evaluation model. The evaluation models were further improved by a consideration of the gender difference in mean skin temperature. The study revealed that the human mean skin temperature could be used as an effective physiological indicator to reflect an individual’s thermal comfort under steady thermal environment. The proposed evaluation model based on mean skin temperature provides an effective and simple method to evaluate an individual’s thermal comfort in a sleeping posture under steady thermal environment.
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The thermoneutral zone is defined as the range of ambient temperatures where the body can maintain its core temperature solely through regulating dry heat loss, i.e., skin blood flow. A living body can only maintain its core temperature when heat production and heat loss are balanced. That means that heat transport from body core to skin must equal heat transport from skin to the environment. This study focuses on what combinations of core and skin temperature satisfy the biophysical requirements of being in the thermoneutral zone for humans. Moreover, consequences are considered of changes in insulation and adding restrictions such as thermal comfort (i.e. driver for thermal behavior). A biophysical model was developed that calculates heat transport within a body, taking into account metabolic heat production, tissue insulation, and heat distribution by blood flow and equates that to heat loss to the environment, considering skin temperature, ambient temperature and other physical parameters. The biophysical analysis shows that the steady-state ambient temperature range associated with the thermoneutral zone does not guarantee that the body is in thermal balance at basal metabolic rate per se. Instead, depending on the combination of core temperature, mean skin temperature and ambient temperature, the body may require significant increases in heat production or heat loss to maintain stable core temperature. Therefore, the definition of the thermoneutral zone might need to be reformulated. Furthermore, after adding restrictions on skin temperature for thermal comfort, the ambient temperature range associated with thermal comfort is smaller than the thermoneutral zone. This, assuming animals seek thermal comfort, suggests that thermal behavior may be initiated already before the boundaries of the thermoneutral zone are reached.
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621 F ollowing the 2007–2008 and 2011 food price crises, renewed concerns over food security have surfaced, in both middle-and high-income regions. In response, the commercial pressures on land are increasing globally 1,2 . Meanwhile access to water is a con-cern, with an ever-increasing number of people affected by water shortages 3 . Energy demand is projected to grow by one-third by 2035, and the prospects for achieving this growth while keeping global temperature increases below 2°C are looking progressively slimmer 4 . This suggests that efficient management and use of these resources will be of utmost importance in the coming decades. At the same time these resources are an integral part of the devel-opment challenge. Close to one billion people are undernourished and another billion are malnourished. At present 1.2 billion people live in areas where there is physical water shortage, a number that is expected to grow in coming decades 3 . A further 1.6 billion people suffer from economic water shortages, where the infrastructure to deliver clean water is not in place. Energy access is also far from uni-versal, with 1.3 billion people living without access to electricity 4 and 2.7 billion with no access to modern and healthy forms of cooking. A key element in management of the land, water and energy systems is that they are inextricably linked. Agriculture alone accounts for 70% of global water withdrawals and industry for another 22%, most of which is for cooling thermal processes in power generation and manufacturing 5
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The worldwide energy consumption in 2006 was close to 498 exajoules. This is equivalent to an energy convergence of 15.8TW into the populated regions, where energy is consumed and dissipated into the atmosphere as heat. Although energy consumption is sparsely distributed over the vast Earth surface and is only about 0.3% of the total energy transport to the extratropics by atmospheric and oceanic circulations, this anthropogenic heating could disrupt the normal atmospheric circulation pattern and produce a far-reaching effect on surface air temperature. We identify the plausible climate impacts of energy consumption using a global climate model. The results show that the inclusion of energy use at 86 model grid points where it exceeds 0.4Wm-2 can lead to remote surface temperature changes by as much as 1K in mid- and high latitudes in winter and autumn over North America and Eurasia. These regions correspond well to areas with large differences in surface temperature trends between observations and global warming simulations forced by all natural and anthropogenic forcings. We conclude that energy consumption is probably a missing forcing for the additional winter warming trends in observations.
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A method was established to evaluate calculation methods of mean skin temperature, in order to find appropriate ones for use in human thermal comfort study. In this method three indexes, including reliability, sensitivity and number of measurement sites, were proposed. Under air temperatures of 21 °C, 24 °C, 26 °C, and 29 °C, 22 subjects’ local skin temperatures (21 sites) and electrocardiograms were measured, and their thermal sensation and thermal comfort were inquired. Human heart rate variability indicated the physiological relation between mean skin temperature and ambient temperature for the sensitivity evaluation. Adopting the evaluation method, 26 types of mean skin temperature calculation methods were evaluated based on the experimental data. The results indicate that a calculation method of mean skin temperature with 10 sites is the most appropriate one, due to its high reliability, excellent sensitivity and fewer measuring sites. When it was applied to reflect thermal comfort, the performance was good.
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One of the uses of ISO 7730 (predicted mean vote, PMV) is to predict the thermal sensations of people in buildings. This application is examined, using the ASHRAE database of field-studies. Taking these world-wide data as a single distribution, PMV is free from serious bias. There exist, however, underlying biases in relation to all contributing variables, and a further bias related to the outdoor temperature. These biases often combine to produce a substantial bias in PMV. In surveys of individual buildings, PMV often differs markedly and systematically from the actual mean vote, both for naturally ventilated (NV) and for air-conditioned (AC) spaces. Possible origins of the biases are discussed, and it is shown that it would be possible to modify PMV substantially to reduce them. Environmental consequences of the use of PMV are discussed. It is concluded that ISO 7730 in its present form can be seriously misleading when used to estimate thermal comfort conditions in buildings.
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The origin and development of the adaptive approach to thermal comfort is explained. A number of recent developments in the application of the theory are considered and the origin of the differences between adaptive thermal comfort and the ‘rational’ indices is explored. The application of the adaptive approach to thermal comfort standards is considered and recommendations made as to the best comfort temperature, the range of comfortable environments and the maximum rate of change of indoor temperature. The application of criteria of sustainability to thermal standards for buildings is also considered.
The 65-node thermoregulation model was developed, based on the Stolwijk model. The model has 16 body segments corresponding to the thermal manikin, each consisting of four layers for core, muscle, fat and skin. The 65th node in the model is the central blood compartment, which exchanges convective heat with all other nodes via the blood flow. Convective and radiant heat transfer coefficients and clothing insulation were derived from the thermal manikin experiments. A thermoregulation model combined with radiation exchange model and computational fluid dynamics (CFD) is proposed. The comprehensive simulation method is described.