Ene gy & Buildings 333 (2025) 115479
A ailable online 16 Feb ua y 2025
0378-7788/© 2025 The Au ho s. Published by Else ie B.V. This is an open access a icle unde he CC BY-NC-ND license (h p://c ea i ecommons.o g/licenses/by-
nc-nd/4.0/).
S uden s’ he mal and indoo ai quali y pe cep ion in seconda y schools in
a Medi e anean clima e
Alicia Alonso
a,*
, Ra ael Su´
a ez
a
, Jesús Llanos-Jim´
enez
a
, Ca men M. Mu˜
noz-Gonz´
alez
b
a
Ins i u o Uni e si a io de A qui ec u a y Ciencias de la Cons ucci´
on, Escuela T´
ecnica Supe io de A qui ec u a, Uni e sidad de Se illa, A . Reina Me cedes, 2, 41012
Se ille, Spain
b
A e y A qui ec u a, Uni e sidad de M´
alaga, Campus Uni e si a io El Ejido, 29071 Malaga, Spain
ARTICLE INFO
Keywo ds:
S uden s’ pe cep ion
The mal com o
Indoo ai quali y
Field su ey
Medi e anean clima e
The mal adap a ion
ABSTRACT
In he wake o he COVID-19 pandemic, he impo ance o achie ing adequa e indoo ai quali y (IAQ) and
add essing i s impac on hyg o he mal condi ions has become pa amoun . En i onmen al quali y in class ooms
signi ican ly in luences s uden s’ heal h, well-being, and academic pe o mance. Na u al en ila ion aces
challenges ela ed o e iciency and he mal com o , e en he de elopmen o ecen s anda ds ocuses on he
con inuous measu emen o CO
2
o enhance heal h and well-being. This s udy add esses a esea ch gap by
simul aneously add essing bo h he mal com o (TC) and IAQ analyses, ocusing on s uden s’ pe cep ions ac oss
seasons in seconda y schools wi hin he Medi e anean clima e o sou he n Spain. A ield s udy conduc ed be-
ween 2022 and 2023 in ol ed long- e m moni o ing and 1,056 su eys om s uden s aged 12–18 in 54
class ooms ac oss se en schools. Da a we e collec ed du ing hea ing and non-hea ing pe iods in na u ally
en ila ed spaces, analysing subjec i e pe cep ions and hei ela ionship wi h objec i e pa ame e s. Resul s
show ha high empe a u es s ongly in luence he mal and ai quali y pe cep ions, while CO
2
le els ha e
minimal impac on Ai Sensa ion Vo ing (ASV), e en a concen a ions exceeding 1,400 ppm. Du ing non-hea ing
seasons, 60 % o s uden s epo ed he mal com o a empe a u es be ween 23-27 ◦C, while discom o
inc eased o 38 % a empe a u es below 19 ◦C du ing hea ing seasons. Neu al empe a u es de i ed om
subjec i e imp essions e eal signi ican seasonal a ia ions. P edic ed Mean Vo e (PMV) unde es ima ed ac ual
sensa ions, pa icula ly du ing cold seasons in wa m clima es. These indings highligh he impac o ou doo
empe a u es on s uden s’ pe cep ions and o e insigh s o e ining com o models and adap ing en ila ion
s a egies o imp o e lea ning en i onmen s in schools.
1. In oduc ion
S uden s spend a signi ican numbe o hou s in class ooms, en i-
onmen s cha ac e ised by high occupan densi y and, o en, ad e se
hyg o he mal and ai quali y condi ions. In some cases in he Medi e -
anean egion, de icien en i onmen al condi ioning sys ems esul in
poo he mal com o (TC) and indoo ai quali y (IAQ) condi ions [1,2].
P olonged exposu e o ad e se indoo en i onmen al condi ions (IEQ)
nega i ely impac s academic de elopmen and long- e m heal h ou -
comes [3–5]. In addi ion, esea ch unde sco es he need o imp o ed
building en elopes o add ess poo insula ion and en ila ion, which
exace ba e o e hea ing isks in Medi e anean clima es. Enhancing he
he mal pe o mance o buildings is essen ial o mi iga ing clima e
change impac s, including he inc easing equency o ex eme hea
e en s [6]. These challenges a e pa icula ly ele an in schools, whe e
high occupan densi y and p olonged exposu e wo sen com o and
heal h ou comes.
The mal com o is closely linked o heal h p oblems [7] and
cogni i e pe o mance, wi h subop imal condi ions educing concen-
a ion and academic p oduc i i y [8,9]. This connec ion unde sco es
he ele ance o Uni ed Na ions Goals, known as Sus ainable De elop-
men Goals, speci ically i e e s o Goal 4, which emphasizes he need o
Abb e ia ions: APD, Ac ual Pe cen age Dissa is ied; ASV, Ai Sensa ion Vo e; IAQ, Indoo Ai Quali y; IEQ, Indoo En i onmen al Quali y; PMV, P edic ed Mean
Vo e; PPD, P edic ed Pe cen age Dissa is ied; Ta, Ai empe a u e; TC, The mal Com o ; TCV, The mal Com o Vo e; TSV, The mal Sensa ion Vo e; Top, Ope a i e
empe a u e; Tou , Ou doo empe a u e; TPV, The mal P e e ence Vo e; T , Radian empe a u e; T m, Mean adian empe a u e.
* Co esponding au ho .
E-mail add ess: [email p o ec ed] (A. Alonso).
Con en s lis s a ailable a ScienceDi ec
Ene gy & Buildings
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h ps://doi.o g/10.1016/j.enbuild.2025.115479
Recei ed 1 Decembe 2024; Recei ed in e ised o m 12 Feb ua y 2025; Accep ed 14 Feb ua y 2025
Ene gy & Buildings 333 (2025) 115479
2
ensu e quali y educa ion in sa e lea ning en i onmen s [10]. In pa allel,
poo IAQ has been iden i ied as a key ac o in he onse o illnesses in
de eloped coun ies [11]. The COVID-19 pandemic u he highligh ed
he signi icance o managing IAQ o mi iga e ai bo ne disease ans-
mission [12], emphasizing he impo ance o managing IAQ in educa-
ional se ings. This si ua ion has p omo ed he de elopmen o
s anda ds such as UNE 171380 [13], ocused on he con inuous mea-
su emen o CO
2
indoo s o imp o e he heal h and well-being o use s,
which esponds o he need o complemen and imp o e he e-
qui emen s es ablished by quali y s anda ds and cu en legisla ion. In
his ega d, p ope en ila ion is c i ical o heal h, as i helps o educe
ai bo ne pollu an s and p e en espi a o y issues. Howe e , na u al
en ila ion comes wi h challenges, including he uncon olled in lux o
ou doo pollu an s, di icul y in ensu ing i s e ec i eness, and po en ial
impac s on ene gy e iciency and he mal com o .
O e ecen decades, esea ch on indoo en i onmen al quali y in
educa ional buildings has wo ked on he analysis o s uden s’ pe cep-
ions o he mal com o o indoo ai quali y [14,15]. In eg a ing hese
subjec i e insigh s wi h objec i e en i onmen al pa ame e s enables he
e inemen o com o models. This adjus men suppo s he de elop-
men o imp o ed na u al en ila ion p o ocols and op imised me-
chanical HVAC sys ems in schools, enhancing o e all en i onmen al
condi ions and s uden well-being.
1.1. Li e a u e e iew
Despi e he in e na ional accep ance o models such as Fange ’s
P edic ed Mean Vo e (PMV) ISO 7730 [16] and ASHRAE 55 [17], hese
models ha e limi a ions. O iginally de eloped o adul o ice wo ke s in
con olled en i onmen s, hey o en ail o accu a ely ep esen he di-
e si y o he mal com o in di e en se ings, pa icula ly schools
[18]. Fu he mo e, clima ic adap a ion ac o s, socio-cul u al and e en
socio-economic ac o s a e only loosely conside ed in many s udies on
indoo en i onmen al quali y, despi e hei po en ial in luence on oc-
cupan s’ com o and heal h. Recen esea ch emphasizes he need o
in eg a e hese aspec s o de elop mo e comp ehensi e and e ec i e
s a egies o imp o ing indoo en i onmen s [19,20].
Acco ding o esea ch, pe cep ions di e depending on pa ame e s
such as clima ic zones o age anges o esponden s. Rome o e al. [21]
e alua ed PMV and The mal Sensa ion Vo e (TSV) in uni e si y class-
ooms in Spain and Po ugal, wi h a Csa clima e in he K¨
oppen-Geige
classi ica ion [22,23]. The indings e ealed ha PMV unde es ima ed
hea sensa ion, wi h a neu al empe a u e (Tn) o 24 ◦C in summe .
Simila ly, To iani e al. [24] ound ha PMV-based eg essions yielded
highe Tn alues (0.8–2.7 ◦C) compa ed o TSV eg essions in Pisa
schools du ing win e . Con e sely, in cold clima es, TSV-based Tn alues
exceed hose based on PMV. S udies also show a ange o accep able
empe a u es ha is bo h highe han in he s a ic model [25] and close
o he adap i e model [26,27,28,29]. S uden s’ he mal awa eness also
de elops wi h age. To iani e al. [30] concluded ha p ima y school
child en lack ull awa eness o hei he mal en i onmen , complica ing
subjec i e assessmen s in younge age g oups.
Unlike he mal com o , whose subjec i e assessmen in ex eme
cases is clea ly iden i ied by he use , indoo ai quali y (IAQ) is ha de
o assess h ough pe cep ion alone. Subs ances like ca bon dioxide
(CO
2
), a subs ance emi ed by occupan s in indoo en i onmen s
commonly used as an IAQ indica o , can cause heal h issues e en a low
concen a ions wi hou being immedia ely no iceable [31,32]. The
s udies by Cabo sk´
a e al. [33] and V´
asquez e al. [34] explo e IAQ in
Swedish school class ooms, wi h an emphasis on en ila ion and i s
impac on child en’s pe cep ion and well-being. While Cabo sk´
a e al.
wo k [33] shows highe pollu an concen a ions in class ooms wi h
na u al en ila ion, V´
asquez e al. [34] ex end his analysis by including
s uden s’ subjec i e pe cep ion. Bo h s udies highligh he impo ance o
adequa e en ila ion s a egies o op imise com o and heal h in
educa ional se ings. Ele a ed CO
2
le els co ela e wi h symp oms like
a igue and discom o , as demons a ed in he s udy o Do izas e al.
[35], which examined nine p ima y schools in G eece (Csa clima e).
Simila ly, Smedje e al. [36], ound ha high le els o espi able dus ,
mould, and bac e ia we e linked o poo e IAQ pe cep ions in 38
Swedish schools (hemibo eal D b clima e) o di e en educa ional
le els. The a o emen ioned s udies a e ca ied ou in di e en clima ic
zones (Csa clima e and D b clima e, espec i ely). In his ega d, Wang
e al. [37] de e mined pe sonal and demog aphic ac o s has in luence
on change o subjec i e indoo ai quali y epo ed by school child en.
The e a e ela i ely ew s udies which de elop a combined analysis
o TC and IAQ app oaches. Resea ch by Ko sa i e al. [38] assessed IAQ
pe cei ed in p ima y schools in he C b (oceanic) clima e o UK, and
ound ha high empe a u es nega i ely impac ed pe cei ed IAQ e en
when CO
2
le els we e wi hin accep able limi s in UK p ima y schools.
O he Medi e anean s udies include he wo k o Dias Pe ei a e al. [25]
also e alua ed he TC and IAQ p e e ences o seconda y school s uden s
du ing mid-season in Po ugal, and Almeida e al. [28], which assessed
pe cep ions in ee- unning schools. Bo h s udies show ha s uden s
ole a e highe indoo empe a u es han ecommended and ha adi-
ional models, like PMV, ail o accu a ely e lec hei he mal sensa-
ions, pa icula ly in non-ai -condi ioned buildings, due o physiological
di e ences be ween child en and adul s. To iani e al. [24,30], which
explo ed he impac o pe cei ed con ol in I alian schools du ing he
hea ing season, highligh ha pe cei ed con ol o e he en i onmen ,
such as opening windows, enhances bo h he mal com o and IAQ
while also educing hea ing ene gy demand in class ooms. These ind-
ings call o ailo ed app oaches o balance com o , en ila ion, and
ene gy e iciency in schools.
Al-Dmou ’s [39] esea ch ca ied ou in he educa ional con ex
s a ed subjec i e assessmen s may no always co espond wi h objec i e
measu es. His indings emphasize he need o a holis ic app oach ha
conside s bo h ype o da a o enhance indoo en i onmen s, ul ima ely
leading o imp o ed occupan sa is ac ion and p oduc i i y in educa-
ional se ings. Table 1 p esen s a e iew o he li e a u e on he
pe cep ual assessmen o he mal com o and ai quali y in class ooms
si ua ed in di e en clima e zones. The able also illus a es he p ima y
a ibu es o he case s udies, including he sample size, le el o edu-
ca ion, and ype o HVAC sys em. In o ma ion on he ype o analysis
ca ied ou (objec i e and/o subjec i e) in o de o de e mine he in-
luence o o he ac o s on pe cep ion, is also included.
The e iew o 23 s udies compiled in Table 1 shows ha sho - e m
measu es, ha co e s one o wo seasons, o in e up ed in e als o e
consecu i e yea s, we e implemen ed in 60 % o cases while only 26 %
o esea ch co e ed wa m and cold seasons simul aneously. Despi e he
ac ha 29 % o hese s udies conduc ed e alua ions om TC and IAQ
app oaches, only one o hem (4 %) ca ied ou an in-dep h analysis om
bo h pe spec i es, al hough i does no calcula e he neu al empe a-
u e. The es o he s udies (78 %) ca ied ou an in-dep h e alua ion o
one o he wo aspec s (TC o IAQ), o ca ied ou a non in-dep h analysis
(15 %) wi hou making compa isons and co ela ions wi h o he
objec i e pa ame e s o subjec i e indices. Limi a ions and gaps in he
s a e o he a can be iden i ied hanks o he e iew o exis ing s udies.
In his espec , mo e a en ion mus be paid o unde s anding s uden s’
pe cep ions o he mal and indoo quali y h ough he ela ionship o
pa ame e s and subjec i e a iables du ing he di e en seasons o he
yea .
1.2. Resea ch objec i e
This s udy aims o imp o e ou unde s anding o s uden s’ pe cep-
ions o he mal com o and indoo ai quali y in ep esen a i e sec-
onda y schools loca ed in he mos ep esen a i e Medi e anean
clima e zones o sou he n Spain. The esea ch makes a signi ican
con ibu ion by using a no el app oach: yea -long measu emen s
co e ing hea ing (3-mon h pe iod in win e ), non-hea ing (3-mon h
pe iod in summe ) and mid-season (3-mon h pe iod in sp ing/au umn)
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
3
Table 1
Summa y e iew o s udies acco ding o clima e zone, HVAC sys ems and desc ip ion o he subjec i e analysis conduc ed.
Re . Case S udies K¨
oppen Clima e
Zone
HVAC TC Subjec i e IAQ Subjec i e
TSV s o he
indices
s
o he
pa am
T
n
ASV s o he
indices
s
o he
pa am
P edominan
pa ame e
Moni o ing Pe iod
Ab eu-
Ha bich
e al. [55]
1 class UN AwB asilia
(B asil)
MV
AC
✓−✓25.9 ◦C− − − −
Sho - e m
measu emen s, wa m
season
Mish a and
Ramgopal
[56]
1 class UN Aw,Kha agpu
(India)
NV ✓ ✓ ✓ 29 ◦C
TSV =0.22 Top −
6.37
− − − −
Sho - e m
measu emen s, mid-
season
Kim and de
Dea , [57]
11P/S.SCH BSh,Aus alia
(New Sou h
Wales)
NVR/
AC
✓ ✓ ✓ 24.4 ◦C
TSV =0.15 Tdi
+0.12
− − − −
Sho - e m
measu emen s, wa m
season
Haddad e al.
[58]
2 S.SCH C a,Aus alia
(Sydney)
NV
AC
✓−✓23.7 ◦C− − − −
Annual
Miao e al.
[59]
16P/S.SCH C a, CsaSpain
(Ca alonia)
NVR ✓ ✓ ✓ 21–25.3 ◦C✓ ✓ −CO
2
Long- e m
measu emen s, wa m
and mid-season
Wu and
Wagne
[29]
1 S.SCH C a,China
(Hengyang)
NV ✓−✓25.7 ◦C summe ,
19.2 ◦C mid-
season,14.9 ◦C
win e
TSV =0.0883 •
Top – 7.13
✓−✓T
Annual
Ko sa i e al.
[38]
29 classes, 8P.SCH C b,UK
(Co en y)
NVR ✓ ✓ ✓ −✓ ✓ ✓ CO
2
Annual
Teli e al. [60] 2P.SCH C b,
UK
(Sou hamp on)
NVR ✓ ✓ ✓ 20.6 ◦C− − − −
Sho - e m
measu emen s, cold
season
Almeida e al
[28]
8 classes, 6 en i e
educa ional ange
CsaPo ugal
(Viseu)
NVR ✓ ✓ ✓ − − − − −
Sho - e m
measu emen s, mid-
season
Apa icio-Ruiz
e al. [27]
3 classes P.SCH CsaSpain
(Se illa)
NVR,
AC
✓ ✓ ✓ − − − − −
Sho - e m
measu emen s, wa m
seasons
Calama e al.
[61]
1 S.SCH CsaSpain
(Se illa)
NV
AC
− − − − ✓− − CO
2
Annual
Dhalluin e al.
[62]
2 class UN Csa,La Rochelle
(F ance)
MV +
HR
R
✓ ✓ ✓ −✓−✓CO
2
Annual
Di Pe na e al.
[63]
1 S.SCH CsaI aly
(Pisa)
MV +
HR
R
✓− − − ✓− − CO
2
Sho - e m
measu emen s, cold
season
Dias Pe ei a
e al. [25]
4 classes S.SCH CsaPo ugal
(Beja)
NVR ✓ ✓ ✓ −✓−✓Ol
Sho - e m
measu emen s, mid-
season
Do izas e al.
[35]
9P.SCH CsaG eece
(A hens)
NVR ✓ ✓ ✓ 18 ◦C✓−✓T
Sho - e m
measu emen s, mid-
season
He acleous
and Michael
[26]
1 class S.SCH Csa
Cyp us (Nicosia)
NVR ✓ ✓ ✓ − − − − −
Annual
Rome o e al.
[21]
29 classes, 3 UN Csa,Spain
(Badajoz)
Po ugal
(Beja)
NVR,
AC
✓ ✓ ✓ 24 ◦C
TSV =0.2908 ⋅
Top −6.9489
✓−✓T
Sho - e m
measu emen s, wa m
season
To iani e al.
[24]
24 classes, 11 schools
ac oss he en i e
educa ional ange
CsaI aly
(Pisa)
NVR ✓ ✓ ✓ 21.7 ◦C
TSV =0.29 •Top
−6.17
− − − −
Sho - e m
measu emen s, cold
season
(con inued on nex page)
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
4
pe iods, combining wi h ield moni o ing and s uden s’ su eys. I
should be men ioned mid-season pe iod was no inco po a ed in his
s udy due o insu icien da a om su eys. This comp ehensi e da ase
allows a de ailed analysis o he mal pe cep ion and ai quali y, allowing
obus compa isons be ween en i onmen al a iables and bo h
pe cei ed and es ima ed pa ame e s. A key inno a ion is he assessmen
o neu al empe a u es de i ed om s uden s’ subjec i e imp essions,
b idging he gap be ween subjec i e expe ience and objec i e me ics.
By in eg a ing hese indings wi h measu able pa ame e s, he s udy
p o ides c i ical insigh s o e ine com o models and ul ima ely guide
he op imisa ion o na u al en ila ion p o ocols and mechanical HVAC
sys em designs in educa ional en i onmen s. This wo k no only ills an
impo an knowledge gap, bu also has p ac ical implica ions o
imp o ing lea ning spaces in simila clima ic egions.
2. Me hods
The me hodology employed in his s udy is de eloped in dis inc
phases which a e illus a ed in Fig. 1 and desc ibed below. The ield
s udy is based on a la ge expe imen al campaign ca ied ou in e mi -
en ly be ween Janua y 2022 and June 2023 in 54 class ooms o 7
educa ional buildings o di e en le els and clima e zones in he sou h
o Spain. The sample comp ised 1056 su eys conduc ed by s uden s,
aged 12 o 18. Da a acquisi ion has been ca ied ou h ough moni o ing
campaigns in bo h hea ing (H) and non-hea ing season (NH) in na u ally
en ila ed class ooms, as well as h ough s uden su eys. Di e en
weeks wi hin each pe iod we e selec ed o he de elopmen o su eys.
Thus, o es ablish a di ec ela ionship wi h he su ey esul s, moni-
o ing da a was selec ed o e he same days we e selec ed. The da a
p ocessing phase was based on a compa ison be ween objec i e a i-
ables and subjec i e ac o s o ac o s es ima ed om he assigned o es.
A s a is ical analysis has been applied o de elop he compa a i e s udy,
consis ing o h ee sec ions. The i s sec ion e alua es he e ec o he
en i onmen al a iables moni o ed on he mal pe cep ion. The second
sec ion hen assesses he e ec o hese a iables on he pe cep ion o ai
quali y. Finally, he hi d sec ion es ablishes he ela ionships ound
Table 1 (con inued)
Re . Case S udies K¨
oppen Clima e
Zone
HVAC TC Subjec i e IAQ Subjec i e
TSV s o he
indices
s
o he
pa am
T
n
ASV s o he
indices
s
o he
pa am
P edominan
pa ame e
Moni o ing Pe iod
To iani e al.
[30]
24 classes, 11 schools
ac oss he en i e
educa ional ange
CsaI aly
(Pisa)
NVR ✓ ✓ ✓ 22.3 ◦C
TSV =0.32 •Top
– 7.13
✓−✓T
IAQV = − 0.119
•Top +2.488
Sho - e m
measu emen s, cold
season
Cabl´
e e al.
[64]
1 S.SCH D b,D ammen
(No way)
MV ✓− − − ✓− − CO
2
Sho - e m
measu emen s, cold
and mid-season
Smedje e al.
[36]
96 classes, 38 en i e
educa ional ange
D b,Sweden
(Uppsala)
MV +
HRR
− − − − ✓−✓Ol
Long- e m
measu emen s, cold
season
Vo nanen-
Winq is
e al. [65]
2 classes, 1P-S.SCH D b,Helsinki
(Finland)
MV +
HRR
− − − − ✓−✓Ol
Sho - e m
measu emen s, wa m
and mid-season
Yang e al.
[66]
5 classes, 1P.SCH D c,Sweeden
(Umeå)
MV +
HRR
✓ ✓ ✓ 20.8 ◦C
TSV =0.155 •
Ta–3.237
− − − −
Long- e m
measu emen s, cold
season
In he TC and IAQ sec ions, compa isons made wi h o he indices (PMV, TPV, e c), and compa isons made wi h objec i e pa ame e s (T, RH and CO
2
) a e indica ed.
E.SCH: Elemen a y School; P.SCH: P ima y Educa ion School; S.SCH: Seconda y Educa ion School; UN: Uni e si y; NV: Na u al Ven ila ion; MV: Mechanical
Ven ila ion; MV +HR: Mechanical Ven ila ion +Hea Reco e y; R: Radia o ; AC: Ai Condi ioning; Ol : Ol ac o y.
Fig. 1. Diag am o he esea ch me hodology.
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
5
be ween he pe cep ual and es ima ed ac o s.
2.1. Case s udy desc ip ion
The p ocess o selec ing and de ining he case s udies o ep esen-
a i e school in he Medi e anean clima e is desc ibed in de ail in he
wo k conduc ed by Llanos e al. [40] and [41]. Howe e , a summa y o
he p ima y da a o be aken in o accoun can be ound in his ex . The
selec ion o he case s udies is based on a mul i-pa ame ic s a is ical
analysis, in eg a ing c i e ia such as clima e zone, yea o cons uc ion,
a chi ec u al ypology, class oom o ien a ion, and building en elope
solu ions. This app oach allows a balanced ep esen a ion o he mos
cha ac e is ic condi ions o he egion.
Based on he K¨
oppen clima e classi ica ion sys em [22], he Anda-
lusian egion is cha ac e ised by he Csa ypology, which co esponds o
a wa m summe Medi e anean clima e. In Spain, he Technical Building
Code (CTE) [42] de ines clima e classi ica ion using a coding sys em ha
combines a le e o win e se e i y (A o E, whe e A indica es he
mildes and E he mos se e e) and a numbe o summe se e i y (1 o 4,
wi h 1 being he mildes ). Fo his s udy, ep esen a i e seconda y
schools om zones A3, B3, B4, C3, and C4 we e selec ed, ep esen ing
he h ee mos common win e clima es (A, B, and C) along wi h he
mos equen summe clima es (le els 3 and 4). The s udy is based on an
analysis o 872 public schools, o which 200 we e selec ed o he
de ailed sample. The dis ibu ion was p opo ional o he clima ic zones
de ined by Spanish egula ions [42]. A chi ec u al and ope a ional
cha ac e is ics we e conside ed, such as na u al en ila ion sys ems and
egula ions applicable a he ime o cons uc ion. This ensu es he
applicabili y o he esul s o eal Medi e anean school con ex s. Fig. 2
shows a mul ipa ame ic pa allel coo dina es g aph o he selec ion o
ep esen a i e seconda y schools. In his Figu e, he ep esen a i e
alues o each c i e ion a e indica ed by ho izon al ba s in g ayscale.
This p ocess yields a lis o ep esen a i e seconda y schools ( anging
om 7 o 9) o each o he i e clima ic zones acco ding o Spanish
egula ions [42].
Table 2 p esen s a summa y o he main cha ac e is ics o he case
s udies, including hei size, and sys ems. All case s udies, which we e
buil p io o he implemen a ion o he p e ailing egula o y s anda d
in Spain, ely on na u al en ila ion as mechanical en ila ion only
became manda o y in schools in Spain in 2007 [43]. In all case s udies
ba one adia o s a e p o ided as a hea ing sys em. Howe e , o eco-
nomic easons, he ac i a ion o he sys em is ypically ese ed o days
wi h ou doo empe a u es below 12 ◦C. Only a limi ed numbe o
selec ed schools ha e cooling sys ems, and hei use is highly
cons ained.
I should be no ed he cons uc ion da e o a building de e mines he
minimum equi emen s and pe o mance s anda ds o i s en elope and
hea ing, en ila ion, and ai condi ioning (HVAC) sys ems. P io o
1979, he e we e no manda o y egula ions go e ning he he mal
pe o mance o building en elopes o en ila ion me hods o con ol
indoo ai quali y. La e on, be ween 1979 and 2005, he i s egula ion
o add ess he he mal ansmi ance and hyg o he mal beha iou o
building en elope elemen s and he building as a whole, as well as he
ai pe meabili y o windows and doo s. The main pa ame e limi ed was
he o e all he mal ansmi ance coe icien o he building.
2.2. Da a acquisi ion
2.2.1. Moni o ing campaign
The objec i e measu emen s consis ed in he acquisi ion o en i-
onmen al pa ame e s in he class ooms du ing one academic yea
(2022–2023). Hyg o he mal and indoo ai quali y pa ame e s we e
analysed ia he moni o ing o he pa ame e s o ai empe a u e (Ta),
We Bulb globe empe a u e (Tg), ela i e humidi y (RH), CO
2
concen-
a ion, pa icula e ma e (PM
2.5
and PM
10
), and o maldehyde (CH
2
O).
The pa ame e s we e moni o ed using a p ope ly ac o y-calib a ed
Sensone Mul isenso SW20 da alogge [44], du ing school hou s in
wo class ooms wi h opposing o ien a ions in each o he se en case
s udies. Da a collec ion was con igu ed o eco d alues a 5-minu e
in e als. The echnical in o ma ion o he equipmen is shown in
Table 3 and ou doo a iables we e aken om Spanish S a e Me eo o-
logical Agency wea he s a ions closes o he case s udy loca ions. Fig. 3
show a plan o a ypical class se up du ing onsi e measu emen s.
Measu emen ins umen s we e in he side sec ion o he class oom
in o de o a oid dis u bing classes and da a collec ion dis o ions due o
windows and doo s and he use o na u al en ila ion.
2.2.2. Su ey model
S uden s’ subjec i e imp essions o class oom en i onmen al quali y
we e collec ed h ough anonymous su eys conduc ed du ing he win e
and summe seasons in he di e en case s udies. A o al o 1,056 su -
eys in 54 class ooms we e collec ed du ing se e al ques ionnai e
campaigns. The sample is balanced in e ms o gende , wi h 52.6 % male
s uden s and 47.4 % emale s uden s. The p ocedu e was implemen ed
in acco dance wi h he guidelines se o h in he Spanish Pe sonal Da a
P o ec ion Law, he eby ensu ing he digi al igh s o he use s su eyed.
As shown in Appendix A, he ou line o he s uden su ey model is
di ided in o h ee blocks. A e p o iding pe sonal da a and some basic
le el segmen a ion pa ame e s such as posi ion in he class oom, e-
sponden s a e equi ed o answe a se ies o ques ions ela ing o he
na u al en ila ion p o ocol o he class oom. In he second block, s u-
den s we e asked o p o ide an o e all e alua ion o he en i onmen al
condi ions o he class oom and o indica e he ype o clo hing wo n in
o de o gua an ee he basic clo hing insula ion [45,17]. The hi d block
collec s da a on s uden s’ judgemen ega ding he mal imp ession and
indoo ai quali y based on ol ac o y pe cep ion, concluding wi h an
o e all assessmen . Ques ions ega ding he mal sensa ions and p e e -
ences we e pu o wa d ollowing he c i e ia commonly used in scales
o assessing he mal en i onmen s acco ding o ISO 10551 [46]. In
o de o es ablish neu al pe cep ions 5- o 7-poin scales we e used.
Addi ionally, s uden s we e asked abou any symp oms o illnesses hey
may su e om. I should be no ed ha he dis ibu ion o hese ques-
ionnai es has he in o med consen o he ele an school au ho i ies.
2.3. Da a p ocessing
2.3.1. Va iables
The analysis o he s uden s’ pe cep ion is based on he associa ion
be ween objec i e en i onmen al a iables, ob ained om onsi e mea-
su emen s, and subjec i e ac o s, de i ed om s uden s’ pe cep ual
o ing.
In ela ion o subjec i e he mal ac o s, and ollowing ISO 7730
[16], indi idual ques ionnai es collec The mal Sensa ion Vo es (TSV)
using a 7-poin a ing scale, om +3 (ho ) o −3 (cold), whe e 0 is
neu al, and The mal P e e ence Vo es (TPV), om +3 (much mo e ho )
o −3 (much mo e cold), whe e 0 is emain unchanged. The mal Com-
o Vo es (TCV) a e collec ed wi h a 5-poin a ing scale, om
‘Com o able’ o ‘Ex emely uncom o able’. The o e all a ing o indoo
ai quali y in class ooms was e alua ed using he Ai Sensa ion Vo e
(ASV) wi h a 5-poin a ing scale, om ‘Accep able’ o ‘Ve y
imp o able’.
The P edic ed Mean Vo e (PMV) index e lec s he a e age alue o
he o es p o ided by a la ge g oup o people o a gi en si ua ion on a 7-
poin he mal sensa ion scale, om +3 (ho ) o −3 (cold), whe e 0 is
neu al. PMV should be used o enclosed, clima e-con olled spaces
en i onmen s wi h cons an occupancy in seden a y o low-in ensi y
ac i i ies. To ensu e he co ec implemen a ion o PMV in his wo k,
in na u ally en ila ed spaces he en ila ion should be con olled. Thus,
he ai eloci y should be wi hin a mode a e ange (0.1 m/s–0.5 m/s) o
main ain an adequa e he mal sensa ion. The p edic ed pe cen age o
dissa is ied (PPD) index p o ides an es ima e o he numbe o occupan s
wi hin a space who would eel dissa is ied by he he mal condi ions. Fo
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
6
Fig. 2. Mul ipa ame ic pa allel coo dina es g aph o he selec ion o ep esen a i e seconda y schools in one o he clima ic zones acco ding o Spanish s an-
da d [54].
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
7
his s udy a JAVA apple ool based on Fange ’s pa ame ic equa ion,
acco ding o ISO 7730 [16], was used o ob ain PMV and PPD h ough
i e a i e calcula ions. The Ac ual Pe cen age o Dissa is ied (APD) index
was calcula ed acco ding o ISO 7730 [16] om he a io be ween he
he mal sensa ion o es (−3, −2) and (+2, +3) and he o al sample size
[47].
The inpu - equi ed eco ded da a ela ing o en i onmen al
condi ions we e he pa ame e s o ambien ai empe a u e (Ta, moni-
o ed a iable), mean adian empe a u e (T , measu ed wi h a we bulb
globe he mome e since he en i onmen is conside ed uni o m and he
su ounding su aces ha e simila empe a u es), ela i e ai eloci y ( ,
ypically es ima ed a ange be ween 0.1 and 0.5 m/s, i is conside ed
0.3 m/s), and ela i e humidi y (RH, moni o ed a iable). O he pa-
ame e s used in he calcula ion ool we e: basic clo hing insula ion
(I
clo
), es ima ed and calcula ed [16,58] om in o ma ion epo ed in
ques ionnai es ega ding he ype o clo hing acco ding o season;
me abolic ene gy p oduc ion (M), conside ing seden a y wo k which
co esponds o 1.2 me ; and a e o mechanical wo k (W, no mally 0).
2.3.2. Neu al and com o empe a u e
The ASHRAE 55 S anda d [17] p o ides a me hodology o calcu-
la ing he op imal indoo com o empe a u e, aking in o accoun he
speci ic cha ac e is ics o he space, occupan s’ ea u es, and p e ailing
en i onmen al condi ions. In o he s udies a linea eg ession analysis is
also p oposed o ob ain he com o empe a u e, al hough he e a e
ce ain limi a ions (sample size and empe a u e ange) which may
a ec he eliabili y o he esul s [48].
O he he mal com o s udies ha e ound ha he abili y o deg ee
o adap a ion o he occupan may a y o e ime, esul ing in a di e en
a e age neu al empe a u e a each s age o he long- e m s udies [49].
The applica ion o G i i h’s me hod [50,21], which is commonly used o
Table 2
Summa y o he main cha ac e is ics o he case s udies.
ID Cons uc ion pe iod Class oom Façade o ien a ion Class oom su ace / olume
(m
2
/ m
3
)
Windows: Su acemax. ape u e
(m
2
)
HVAC sys ems*Numbe o s uden s
CS 1 1979–2005 SE-NW 54.9 / 164.7 10.2 (5.1) Radia o s 30
CS 2 <1979 SE-NW 57 / 171.1 9.4 (4.7) None 29
CS 3 1979–2006 SE-NW 45.8 / 126 13.3–9.8
(6.6–4.9)
Radia o s + ans 26
CS 4 <1979 SE-NW 41.6 / 131 7.3 (3.6) Radia o s +Spli s 25
CS 5 1979–2005 S-W-N 47.2 / 141.6 6.4 (3.2) Radia o s +Spli s 30
CS 6 <1979 E-W 52.2 / 156.6 8.2 (4.1) Radia o s + ans 31
CS 7 1979–2005 S-N 57.7 / 173.2 8.4 (4.2) Radia o s + ans 31
*
All case s udies ha e only na u al en ila ion h ough he opening o windows (usually sliding) and doo s, some o hem wi h high windows on o he co ido .
Table 3
Moni o ing equipmen cha ac e is ics.
Scope Pa ame e s Uni s Range Accu acy
IAQ CO
2
Ca bon dioxide ppm 0 a
5000
±10 %
CH
2
O Fo maldehyde mg/
m
3
0 a 6.25 ±0.03 mg/m
3
PM
2.5
2.5 µm Pa icula e
Ma e
µg/
m
3
0 a
1000
±15 µg/m
3
<
100 ±15 % >
100PM
10
10 µm Pa icula e
Ma e
µg/
m
3
Hyg o-
he mal
Tg Globe
Tempe a u e
◦C−20 a
+65
±0.5 %
Ta Ai Tempe a u e
RH Rela i e
Humidi y
% 0 a 100 ±3 %
Fig. 3. Plan o a ypical class se up du ing moni o ing campaign.
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
8
de i e he mal sensi i i y, is based on ob aining he com o empe a-
u e (Tc) om he ollowing Eq. (1):
Tc =Top −TSV
G(1)
whe e Top is he ope a i e empe a u e, which is ob ained om he
a e age o he ai empe a u e (Ta) and he mean adian empe a u e
(T m). TSV is he The mal Sensa ion Vo e and G is he G i i h cons an ,
which is usually aken o be cons an a 0.5 ◦C [51,21,62]. When TSV is
equal o 0, he com o empe a u e (Tc) ob ained e e s o he neu al
empe a u e (Tn) o he occupan s.
2.3.3. S a is ical analysis
Da a collec ed in he ques ionnai es on he subjec i e pe cep ion o
he s uden s was assessed by means o s a is ical analysis. Two main da a
analysis echniques we e used in he s udy, classi ied as p edic i e and
co ela ional assessmen . Linea eg ession jus i ies and p edic s he
ela ionship be ween di e en dependen and independen a iables.
The R
2
coe icien o de e mina ion indica es he p opo ional amoun o
a ia ion in he esponse a iable explained by he eg ession model.
In his esea ch, co ela ions and eg essions a e used o show how
he subjec i e a iables TSV, TPV, TCV and ASV a e ela ed o objec i e
pa ame e s such as T and CO
2
le els. Pea son’s co ela ion pa ame ic
es has been used o measu e he s eng h and di ec ion o he linea
ela ionship be ween wo a iables. Pea son’s co ela ion coe icien (R)
is ela ed o he slope o he linea eg ession (β1) and he coe icien o
de e mina ion (R
2
), which measu es he p opo ion o he a iabili y in
he y da a ha is explained by he eg ession model. In his s udy, he
s eng h o he co ela ions was classi ied based on he ollowing in-
e als o Pea son’s R: e y low (R =0.00–0.19), low (R =0.20–0.39),
mode a e (R =0.40–0.59), high (R =0.60–0.79), and e y high (R =
0.80–1.00). In o de o ensu e eliabili y and accu acy o he su ey
esul s, a i s s ep ocused on a p ocess disca ding inconsis en e-
sponses. This ask consis ed o a co ela ion be ween esponses. Th ee
ques ions wi h sligh ly di e en app oaches o he mal com o a e used
o iple check he consis ency o esponden s’ answe s. The no mali y
dis ibu ion o he da a, which de e mines whe he pa ame ic o non-
pa ame ic es s a e used, mus also be e i ied. In his ega d, g aph-
ical me hods such as his og am plo ing, ep esen ing he in e al-scale
da a, a e used o ca y ou he no mali y analysis.
3. Resul s
The esul s objec i ely eco ded h ough con inuous moni o ing o
pa ame e s, as well as he subjec i e o es o he s uden s ega ding
hei he mal pe cep ion and indoo ai quali y in he class oom, a e
p esen ed in his sec ion. Da a was depic ed and o ganised o enable he
analysis o di e en e ec s o en i onmen al a iables on he s uden s’
imp essions. The da a collec ed om he ques ionnai es we e hen
classi ied acco ding o clima ic a ea and season o he yea in o de o
p o ide an o e iew o a ia ions esul ing om he case s udy
loca ions.
The en i onmen al pa ame e alues moni o ed a he ime o he
su ey in each o he case s udies, as well as he subjec i e indices ob-
ained om he su eys ca ied ou , a e shown in Table 4 (hea ing
season) and Table 5 (non-hea ing season). Mean o e e e s o he mean
alue ob ained indi idually pe class oom (i.e. o al sum o he o es by
he numbe o s uden s aking he su ey).
3.1. In e ac ion be ween moni o ed and su eyed a iables
3.1.1. The mal pe cep ion
In Fig. 4a), pe cen age o o es o ‘ e y cold/cold’ (TSV = − 3 and
−2), ‘neu al’ (TSV = − 1, 0 and 1), and ‘ho / e y ho ’ (TSV =2 and 3)
we e plo ed agains indoo empe a u e, and Fig. 4b and c) plo ed
he mal sensa ion o es agains CO
2
le els du ing non-hea ing (NH)
(Fig. 4b) and hea ing (H) (Fig. 4c) seasons. A p opo ion o 100 % co -
esponds o all s uden s o each su ey. Simila ly, Fig. 5 shows he
Table 4
Summa y o da a collec ed a he ime o he su ey du ing he hea ing season (H).
Case s udy O ien a ion Tou (◦C) Ta (◦C) T m (◦C) HRm (%) CO
2
(ppm) N◦o s uden s Mean Vo e PMV
TSV TCV TPV ASV
CS1 NW(*) 7.7 18.3 17.7 37 1364 22 −0.8 1.7 0.9 2.14 −0.88
SE 9 19.3 18.9 34 997 21 −1.5 2.8 1.0 2.76 −0.67
CS3 NW(*) 12.2 18.9 20.9 44 756 23 −0.6 1.7 0.6 1.91 −0.84
12.2 18.9 20.9 44 756 21 0.4 1.4 0.1 2.48 −1.03
SE 12.2 20.2 20.2 43 857 28 −0.4 1.5 0.7 1.82 −0.88
12.2 20.2 20.2 43 857 20 −0.2 1.3 0.3 2.55 −1.31
CS4 NW(*) 7.9 18.9 18.9 39 430 21 −0.3 1.6 0.6 1.86 −1.04
7.8 18.8 18.8 38 400 13 −0.3 1.3 0.8 1.69 −1.50
SE 7.8 21.6 21.6 36 751 17 −0.1 1.4 0.2 1.71 −0.73
7.9 21.5 21.5 36 746 16 −0.5 1.6 0.7 1.69 −0.14
NW(*) 17.5 23.1 21.5 57 723 19 0.2 1.4 −0.3 1.84 −0.32
SE 17.5 23.2 24.4 59 897 20 0.0 1.4 −0.2 2.25 0.01
NW(*) 3.8 15.5 18.6 37 678 15 −0.5 1.5 1.1 1.87 −1.24
4.9 17.9 16.1 40 1590 22 −0.5 1.4 0.8 1.86 −1.07
SE 3.8 16.9 17.7 35 605 16 −0.9 1.8 0.8 2.56 −1.29
4.9 19.2 15.3 36 1481 28 −0.6 1.6 1.1 1.96 −0.96
CS5 N 10.6 19.3 24.2 36 557 15 −0.1 1.4 0.3 2.47 −0.69
W 10.6 19.3 24.2 36 557 19 −0.6 1.6 0.7 1.68 −0.69
S 10.6 20.2 23.1 34 416 20 −0.2 1.3 0.2 1.70 −0.65
10.6 20.5 22.7 35 570 21 −0.1 1.5 0.2 2.29 −0.47
CS6 E 3.5 15.2 17.0 43 606 17 −0.9 1.8 0.8 2.29 −1.38
3.5 15.2 17.0 43 606 19 −0.2 1.4 0.5 2.00 −1.38
W 3.1 14.1 16.3 46 624 17 −0.8 1.5 0.5 1.35 −1.79
3.5 15.4 15.0 45 771 22 −0.2 1.1 0.4 2.36 −1.70
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
9
p opo ion o s uden s who desc ibed hemsel es as eeling ‘com o -
able’ (TCV =1), ‘uncom o able’ (TCV =2 and 3) o ‘ e y uncom o -
able’ (TCV =4 and 5) plo ed agains Ta (Fig. 5a) and CO
2
le els (Fig. 5b
and c). In pa allel, he ela ionships be ween pa ame e s obse ed in
Figs. 4 and 5 a e suppo ed by he s a is ical me ics lis ed in Tables 6
and 7. These da a allow quan i a i e con i ma ion o he exis ence o
s a is ically signi ican ela ionships.
Based on linea eg essions o he sensa ion p opo ions, plo ing he
esul s in Fig. 4a) illus a es how empe a u e a ia ions a ec he use ’s
pe cep ion o hea . I can be seen ha he inc ease in empe a u e in he
class oom leads o a signi ican inc ease in ‘ho ’ o es, eaching almos
70 % o he p opo ions. This impac can be quan i ied om he R
2
alue, which sugges s ha 64 % o he a ia ions in ’ho / e y ho ’ o es
a e due o he inc ease in empe a u e, while con e sely, he dec easing
slope o he neu al o es sugges s ha 48 % o he a ia ions a e caused
by he a ia ion in he he mal pa ame e . The ela ionship be ween
sensa ion o e and empe a u e show a s ong signi ican co ela ion (p
<0.05, Table 6).
The in e sec ion be ween he linea eg ession models shows ha a a
empe a u e o 30.5 ◦C he pe cen ages o ho and neu al o es a e he
same, which means ha hal o he s uden s pe cei e a neu al en i-
onmen while he o he hal pe cei e a ho en i onmen . The in e -
sec ion be ween eg essions o ho and cold o es a a empe a u e o
20.5 ◦C can be seen om he join ep esen a ion o win e and summe
ou comes, he esul s o which appea in he same igu e. Tempe a u e
anges a y be ween 14.1–23.2 ◦C du ing he H season and 23.3–34.7 ◦C
du ing he NH season. In his ega d, he ype o clo hing wo n in he
di e en seasons may de e mine a small pe cen age o he o es (10 %)
eeling wa m in win e and cool in summe .
The e ec o a ying CO
2
concen a ion on TSV can be analysed in
Fig. 4b. The esul s show no meaning ul ela ionship be ween he wo
ac o s, as can also be con i med in iew o he Pea son R alues, which
show a low o e y low co ela ion (R <0.40) in he Table 6. A high
concen a ion o mo e han 70 % ’neu al’ o es is obse ed i espec i e
o he CO
2
concen a ion. A dec ease in he eeling o wa m h du ing NH
and a sligh inc ease in he eeling o cold is obse ed as he CO
2
con-
cen a ion inc eases du ing H season. Based on s uden s’s esponses, i
can be con i med ha on he coldes days (Tou be ween 3 and 4.9 ◦C)
windows we e closed and hea ing sys em was no ac i a ed (Ta be ween
14 and 16 ◦C). Du ing hese days CO
2
concen a ions we e highe , which
is why an inc ease o “cold o es” is obse ed. On he o he hand, du ing
he NH season he windows we e open, e en on days wi h Tou abo e
33 ◦C, and no HVAC sys ems we e ac i a ed, so “ho o es” inc eased
wi h low CO
2
concen a ions.
When assessing he ela ionship be ween en i onmen al a iables
and he TCV, a clea ela ionship be ween occupan com o and em-
pe a u e a ia ion is iden i ied (Fig. 5a). As he empe a u e inc eases,
he eeling o com o dec eases, eaching 21 % ‘ e y uncom o able’
when empe a u es exceed 34 ◦C. Simila ly, he mal discom o and
empe a u e inc ease p opo ionally. I can be seen ha 40 % o s uden s
a e ‘com o able’ a a empe a u e o 27 ◦C, and he linea eg ession o
he ’com o able’ model in e sec s wi h he ’uncom o able’ model a a
empe a u e o 25.5 ◦C, wi h a p opo ion o 44 %, and wi h he ’ e y
uncom o able’ model a a empe a u e o 34.2 ◦C, wi h a p opo ion o
23 %.
As wi h TSV, he e is no ela ionship wi h TCV as he CO
2
le el in-
c eases. The mal com o is main ained a a a e o 50 %, e en a le els
abo e 1300 ppm du ing H season (Fig. 5c). This con i ms he indepen-
dence o he mal pe cep ion in ela ion o CO
2
le els (s eng h o co -
ela ion low o e y low wi h R below 0.25, Table 7).
When anking he TCVs a di e en empe a u e anges di ec ly
ela ed o he empe a u e o he s a ic com o models [16]. Fig. 6a)
shows ha a a empe a u e below 23 ◦C, 57.36 % o he ’com o able’
o es a e main ained. I is only abo e 27 ◦C, conside ed discom o in
Table 5
Summa y o da a collec ed a he ime o he su ey du ing he non-hea ing season (NH).
Case s udy O ien a ion Tou (◦C) Ta (◦C) T m (◦C) HRm (%) CO
2
(ppm) N Mean Vo e PMV
TSV TCV TPV ASV
CS1 NW(*) 21.2 24.7 24.5 59 406 24 0.5 1.5 −0.4 2.58 −0.75
SE 20.4 25.5 25.5 54 769 14 0.4 1.6 −0.2 2.14 −0.44
CS2 NW(*) 30.4 28.6 28.0 37 447 10 1.2 1.8 −1.1 2.20 0.56
SE 32 29.2 29.4 35 424 10 1.1 1.7 −0.8 2.10 0.90
CS3 NW(*) 34.3 32.5 38.2 31 503 26 2.3 3.0 −1.6 2.77 3.11
34.3 32.6 38.1 33 495 30 2.6 3.5 −1.7 3.60 3.15
SE 34.3 32.6 32.6 31 484 24 2.4 3.3 −1.5 3.79 2.41
34.3 32.9 32.9 33 475 25 2.5 2.8 −1.3 3.08 2.31
CS4 NW(*) 34.9 34.6 34.0 29 585 12 2.7 3.6 −1.8 3.08 2.90
SE 34.9 33.4 33.8 32 545 11 0.8 1.6 −0.9 2.18 2.60
34.9 33.4 33.8 33 546 24 2.0 2.8 −1.4 2.33 2.62
CS5 N 26.3 28.5 29.7 38 1470 11 1.7 2.2 −1.2 3.27 0.63
W 26.3 25.8 32.5 38 1470 10 1 1.7 −1.1 2.20 0.50
S 26.3 29.5 30.7 39 831 15 1.2 1.9 −1.2 3.00 1.08
CS6 E 23.5 26.1 26.1 34 618 27 0.5 1.5 −0.3 2.22 −0.37
23.9 26.1 26.1 34 618 29 0.6 1.4 −0.6 2.28 −0.65
23.9 26.1 26.1 35 600 18 1.8 2.5 −1.1 2.78 −0.64
W 2.5 25.1 25.1 34 600 32 0 1.1 0 1.97 −1.08
E 28.6 26.5 26.5 43 509 30 −0.1 1.4 0.1 3.00 0.09
W 28.6 25.5 25.5 41 509 27 0.3 1.2 −0.1 2.44 −0.08
CS7 N 29 28.8 27.2 31 517 23 0.7 1.5 −0.5 2.35 0.22
S 29 29.8 28.2 34 814 22 1.5 2.1 −1 2.27 1.67
N 24.8 23.3 22.7 50 786 23 0.3 1.9 −0.2 2.78 −0.84
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
16
4.3. S uden s’ pe cep ions e sus p edic i e com o indices
A compa ison o he mean alues o he mal p e e ence and he mal
sensa ion e ealed a low dispe sion o esul s. The co ela ion index
be ween bo h ac o s is 0.92, which means ha only 8 % o he esul s
a e no in pe ec ag eemen (Fig. 14 a). The co ela ion be ween he wo
pa ame e s is mo e p onounced when he wind chill is ho . In his case, a
gene al p e e ence o sligh ly coole en i onmen s was obse ed, as
MTS = − 1.5 co esponds o he he mal p e e ence MTP =2.5.
Fig. 14 b) shows he ela ionship be ween he es ima ed mean o e
PMV and he ac ual he mal sensa ion MTS. Al hough he slope o he
models ollow a simila end, he ela ionship is a om pe ec ,
especially o a neu al es ima ed o e (MTS be ween −1 and 1), whe e
he esul s a e qui e sca e ed owa ds a cold he mal sensa ion (PMV
−2). Acco ding o he co ela ion index, unde 30 % o he o es ma ch
hei es ima e. This esul s in a coole o e being es ima ed han wha is
ac ually exp essed by he occupan s, ha is o say, he TSV model has
o e es ima ed he p edic ed sensa ion. This inding is in ag eemen wi h
he conclusions ob ained in s udies ca ied ou in o he a eas wi h he
same clima ic condi ions [21].
5. Limi a ions and u he wo k
The geog aphical scope o his s udy e e s o ep esen a i e
Fig. 11. Analysis o pa ame e s a ec ing ASV.
Fig. 12. Ai Sensa ion Vo es (ASV) s. The mal Sensa ion Vo es (TSV) acco ding o The mal Com o Vo es (TCV) o each season.
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
17
seconda y schools in Andalusia. Expanding he s udy o schools in
di e se egions could p o ide b oade insigh s in o he in e play be-
ween en i onmen al ac o s and s uden com o . Addi ionally, ac o s
such as building o ien a ion, educa ional le el, and long- e m exposu e
o a ying condi ions can be ex ensi ely explo ed in u he wo k.
The s udy’s eliance on he PMV model exposed disc epancies be-
ween p edic ed and ac ual com o sensa ions. This unde lines he need
o e ine com o models o be e e lec local clima es and he
Table 9
P oposed TSV and PMV eg ession equa ions and neu al empe a u es.
Season Indices Equa ion R
2
p- alue Tn A e age
TSV/PMV APD/PPD (%)
All yea TSV TSV =0.1625*T
a
-3.3458 0.79 <0.05 21.3 0.34 24.00
PMV PMV =0.2163*T
a
-5.1731 0.83 <0.05 23.9 −0.20 34.22
Non-Hea ing TSV TSV =0.2084*T
a
-4.7735 0.65 <0.05 22.9 1.22 41.50
PMV PMV =0.4017*T
a
-10.681 0.92 <0.05 26.6 0.87 40.97
Hea ing TSV TSV =0.0676*T
a
-1.6769 0.17 0.1 24.8 −0.40 13.05
PMV PMV =0.1613*T
a
-3.9777 0.73 <0.05 24.7 −0.94 27.46
Fig. 13. Rela ionship be ween indoo ope a i e empe a u e (Ta) and s uden s’ pe cep ion (TSV-PMV).
Fig. 14. a) The mal sensa ion s. he mal p e e ence mean alues (MTS and MTP); b) he mal sensa ion mean alues (MTS) s. P edic ed Mean Values (PMV).
A. Alonso e al.
Ene gy & Buildings 333 (2025) 115479
18
adap abili y o popula ions.
In alignmen wi h EU sus ainabili y goals, u u e esea ch should
explo e ene gy-e icien adap i e com o s a egies and e alua e hei
esilience unde clima e change scena ios. By add essing hese limi a-
ions, u u e wo k can con ibu e o de eloping sus ainable and heal hy
indoo en i onmen s in schools.
6. Conclusions
This s udy conduc ed a comp ehensi e assessmen o s uden s’
he mal and indoo ai quali y pe cep ion in ep esen a i e seconda y
schools in he Andalusian egion. The esul s a e based on a moni o ing
campaign ca ied ou o e an en i e yea and ques ionnai es collec ed
du ing in e mi en pe iods o wa m and cold seasons. Linea eg ession
models we e used o analyse he e ec o en i onmen al a iables on he
ac ual subjec i e indices, calcula ed om he esponses collec ed in he
su eys. The ela ionships be ween pe cep ual and es ima ed ac o s
(PMV) we e also assessed. Based on he indings o his wo k, he
ollowing conclusions can be highligh ed:
- Rega ding he mal pe cep ion:
o A highe ole ance o ex eme empe a u es du ing non-hea ing
season is obse ed, as 60 % o occupan s emain he mally
com o able up o a empe a u e o 27 ◦C, and only 23 % desc ibed
hei pe cep ion as e y uncom o able a 34 ◦C. Du ing hea ing
season, discom o alues a e close o 40 % a a empe a u e below
19 ◦C.
o Va ia ions in CO
2
le els do no a ec he he mal pe cep ion o he
occupan s.
- Rega ding indoo ai quali y pe cep ion:
o High empe a u es eco ded du ing non-hea ing season has a sig-
ni ican e ec on ai quali y, since a a empe a u e abo e 27 ◦C
he e is a d as ic inc ease in ’ e y imp o able’ o es, which each
30 % o he o al.
o Va ia ions in CO
2
le els we e conside ed i ele an , especially
du ing pe iods o ex eme hea . E en he highes o e accep ance
is eco ded a CO
2
le els abo e 1400 ppm.
- Rega ding he ela ionship be ween ac ual and p edic ed ac o s:
o The p edic ed o e unde es ima ed he ac ual o e wi h PMV
alues lowe han he mal sensa ion. This de e mined a poo
p edic ion o s uden s’ ac ual wind chill du ing cold season in
wa m clima es.
o High ou doo empe a u es led o highe neu al empe a u es
being ob ained han in o he s udies ca ied ou in a Medi e a-
nean clima e. Neu al empe a u e alues we e quan i ied a
22.9 ◦C o he mal sensa ion, and 26.6 ◦C o he PMV du ing
wa m season.
In iew o he conclusions, in e es ing obse a ions a e made
ega ding he s ong in luence o clima e on he en i onmen al
pe cep ion, bo h he mal and indoo ai quali y. This inding aises an
impo an poin abou how eal-wo ld condi ions, such as high ou doo
empe a u es and acclima iza ion o wa me clima es, may lead o de-
ia ions om he es ablished com o models. This sugges s ha com o
h esholds migh be mo e lexible in wa me en i onmen s, especially in
egions whe e indi iduals a e exposed o high empe a u es egula ly.
This obse a ion could be use ul o e ining com o models o be e
accoun o local clima e condi ions and he adap abili y o he
popula ion.
In summa y, while he esul s exceed ypical com o model p e-
dic ions, hey p o ide aluable insigh s in o how com o pe cep ions
can a y in speci ic clima ic condi ions, sugges ing a need o adap
exis ing models o e lec eal-wo ld he mal expe iences.
All au ho s ha e ead and ag eed o he published e sion o he
manusc ip .
CRediT au ho ship con ibu ion s a emen
Alicia Alonso: W i ing – e iew & edi ing, W i ing – o iginal d a ,
Valida ion, So wa e, Me hodology, In es iga ion, Fo mal analysis, Da a
cu a ion, Concep ualiza ion. Ra ael Su´
a ez: W i ing – e iew & edi ing,
Visualiza ion, Valida ion, Supe ision, P ojec adminis a ion, Me hod-
ology, In es iga ion, Funding acquisi ion, Fo mal analysis, Concep u-
aliza ion. Jesús Llanos-Jim´
enez: W i ing – e iew & edi ing, So wa e,
Me hodology, In es iga ion, Funding acquisi ion, Fo mal analysis, Da a
cu a ion, Concep ualiza ion. Ca men M. Mu˜
noz-Gonz´
alez: W i ing –
e iew & edi ing, Visualiza ion, Me hodology, In es iga ion, Da a
cu a ion.
Decla a ion o compe ing in e es
The au ho s decla e ha hey ha e no known compe ing inancial
in e es s o pe sonal ela ionships ha could ha e appea ed o in luence
he wo k epo ed in his pape .
Acknowledgemen and unding
The au ho s wish o acknowledge he inancial suppo p o ided by
G an (PID2020-117722RB-I00) “Re o i en ila ion s a egies o
heal hy and com o able schools wi hin a nea ly ze o-ene gy building
ho izon” unded by MCIN/AEI/10.13039/501100011033; as well as
me eo ological da a p o ided by he S a e Me eo ological Agency
(AEMET). In addi ion, he au ho J.Ll-J. g a e ully acknowledges he
unding ecei ed by he Minis y o Uni e si ies h ough he Uni e si y
Teache T aining Con ac G an P og amme (FPU20/04393).
Appendix A. Supplemen a y da a
Supplemen a y da a o his a icle can be ound online a h ps://doi.
o g/10.1016/j.enbuild.2025.115479.
Da a a ailabili y
Da a will be made a ailable on eques .
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