Academic Edi o : Cons an inos A.
Bala as
Recei ed: 13 Ma ch 2025
Re ised: 2 Ap il 2025
Accep ed: 4 Ap il 2025
Published: 6 Ap il 2025
Ci a ion: Lopez Ca eño, R.D.;
Pa do-Bosch, F.; Aida o , S.; Boix-Co s,
D.; Pujadas, P. A Simpli ied Class oom
Indoo Ai Quali y Risk Index:
Applica ion in he Medi e anean
Region o Suppo he Enhanced Design
o Educa ional En i onmen s. Appl. Sci.
2025,15, 4033. h ps://doi.o g/
10.3390/app15074033
Copy igh : © 2025 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license
(h ps://c ea i ecommons.o g/
licenses/by/4.0/).
A icle
A Simpli ied Class oom Indoo Ai Quali y Risk Index:
Applica ion in he Medi e anean Region o Suppo he
Enhanced Design o Educa ional En i onmen s
Ruben Daniel Lopez Ca eño 1,2 , F ancesc Pa do-Bosch 1,2 , S anisla Aida o 1,2 , Da id Boix-Co s 3
and Pablo Pujadas 1,2,*
1G oup o Cons uc ion Resea ch and Inno a ion (GRIC), C/Colom, 11, Ed. TR5, 08222 Te assa, Spain;
[email p o ec ed] (R.D.L.C.); ancesc.pa [email p o ec ed] (F.P.-B.); s anisla [email p o ec ed] (S.A.)
2Depa men o P ojec and Cons uc ion Enginee ing, Uni e si a Poli ècnica de Ca alunya Ba celona
Tech (UPC), A . Diagonal 647, 08028 Ba celona, Spain
3Depa men o Ci il and En i onmen al Enginee ing, Uni e si a Poli ècnica de Ca alunya Ba celona
Tech (UPC), c/Jo di Gi ona 1–3, 08028 Ba celona, Spain; [email p o ec ed]
*Co espondence: [email p o ec ed]
Abs ac : The quali y o indoo en i onmen s wi hin educa ional se ings signi ican ly
impac s he heal h, sa e y, and com o o occupan s. In his manusc ip , a simpli ied
Class oom Indoo Ai Quali y (CIAQ) Risk Index, aimed a assessing he po en ial abili y
o class ooms o main ain CO
2
le els wi hin accep able limi s, is in oduced. Comp ising
h ee p ima y componen s— he likelihood o su passing p ede ined CO
2
h esholds, he
po en ial numbe o indi iduals exposed, and he class oom’s capaci y o wi hs and o mi -
iga e h ea s— his index se es as a aluable compliance ool du ing bo h he design phase
and ope a ional managemen o educa ional spaces. Addi ionally, apa om p esen ing
he index amewo k, a sensi i i y case s udy analysis is ca ied ou o e i y he sui abili y
o he p oposed me hod and he sensi i i y o he ac o s in ol ed. Th ough his analysis,
he obus ness o he CIAQ Risk Index in a ious scena ios is demons a ed. By quan i ying
and e alua ing po en ial isks associa ed wi h indoo ai quali y, he CIAQ Risk Index
con ibu es o ongoing e o s o c ea e heal hie indoo en i onmen s. Fu he mo e, i
acili a es he iden i ica ion o budge a y mi iga ion s a egies ha should posi i ely a ec
he ai quali y; among hose, an in e en ion, e o i ing, and en ila ion imp o emen s
can be lis ed. Th ough p oac i e isk iden i ica ion and app op ia e ac ions, including
egula ion adjus men s and en ila ion s a egies, he educ ion in heal h p oblems, he
enhancemen o well-being, and he imp o emen o o e all pe o mance and quali y o
li e o educa ional communi ies can be achie ed.
Keywo ds: indoo ai quali y; class oom en i onmen ; isk assessmen ; IAQ isk managemen ;
en ila ion s a egies
1. In oduc ion
In educa ional se ings, inadequa e indoo ai quali y (IAQ) has been widely ec-
ognized as a key ac o a ec ing s uden s’ heal h, cogni i e pe o mance, and o e all
academic ou comes [
1
–
3
]. Va ious s anda ds es ablish h eshold alues o ca bon dioxide
(CO
2
)—a gas p ima ily p oduced by occupan s’ espi a ion—as an indica o o en ila ion
adequacy. Exceeding concen a ions o 1000 pa s pe million (ppm) sugges s po en ial ai
quali y issues. P olonged exposu e o ele a ed CO
2
le els can con ibu e o s agnan indoo
en i onmen s, igge ing symp oms associa ed wi h Sick Building Synd ome (SBS), such as
Appl. Sci. 2025,15, 4033 h ps://doi.o g/10.3390/app15074033
Appl. Sci. 2025,15, 4033 2 o 15
headaches [
4
,
5
], a igue [
6
], eye i i a ion [
4
], educed concen a ion [
7
], impai ed cogni i e
pe o mance [
8
], decision-making di icul ies [
9
], and espi a o y ac symp oms [
10
],
while also inc easing suscep ibili y o ai bo ne in ec ions.
The COVID-19 pandemic u he highligh ed he impo ance o managing IAQ in
educa ional buildings [
11
,
12
]. Howe e , nume ous s udies conduc ed be o e and a e
he pandemic ha e shown ha indoo CO
2
concen a ions in class ooms o en exceed
ou doo le els— anging om 350 o 2500 ppm [
13
–
16
]—and may su pass 4000–4500 ppm
in some cases [
17
,
18
]. Fo example, Díaz e al. [
19
] epo ed ha indoo CO
2
le els exceeded
ecommended h esholds du ing 70% o school hou s in win e ac oss eigh Chilean schools.
Miao e al. [
20
] ound ha CO
2
concen a ions in 32 Spanish class ooms a e aged 1194 ppm
du ing win e , wi h abou hal o he eaching ime exceeding na ional limi s. Simila ly,
Vassella e al. [21] ound ha nea ly wo- hi ds o one hund ed Swiss class ooms ailed o
mee IAQ s anda ds, while Cai e al. [
22
] obse ed ha bo h mechanically and na u ally
en ila ed class ooms in China equen ly exceeded CO2limi s.
These indings emphasize he c i ical need o e ec i e IAQ managemen in edu-
ca ional se ings, bo h du ing he design phase and in ongoing ope a ion [
9
,
23
]. In his
con ex , he p esen s udy p oposes a simpli ied Class oom Indoo Ai Quali y (CIAQ) Risk
Index as a p ac ical ool o assessing he po en ial o a class oom—designed o speci ic
occupancy and ac i i y pa e ns— o main ain CO2le els wi hin accep able limi s.
The CIAQ Risk Index se es as a decision-suppo ool ha in eg a es key pa ame-
e s such as occupancy, ac i i y le el, en ila ion capaci y, and spa ial cha ac e is ics o
es ima e he isk o exceeding CO
2
h esholds. I enables ea ly iden i ica ion o high- isk
class ooms and suppo s p oac i e planning by school adminis a o s, designe s, and
acili y manage s. When applied du ing he design phase, he index allows use s o explo e
a ious “le e s” such as occupancy limi s, en ila ion s a egies, ac i i y ypes, and oom
dimensions, helping o iden i y op imal con igu a ions be o e cons uc ion o e u bish-
men begins. In exis ing buildings, i in o ms a ge ed in e en ions—such as en ila ion
upg ades, schedule modi ica ions, o occupancy adjus men s—aimed a imp o ing ai
quali y ou comes.
The index is buil on h ee co e componen s: (1) he likelihood o CO
2
le els exceeding
p ede ined h esholds (haza d); (2) he numbe and sensi i i y o indi iduals po en ially
exposed o hose condi ions (exposu e); and (3) he class oom’s abili y o mi iga e o
wi hs and he impac o hose condi ions ( ulne abili y).
By quan i ying hese componen s, he CIAQ Risk Index con ibu es o ongoing e o s
o imp o e IAQ in schools. Beyond iden i ying high- isk si ua ions, i also suppo s b oade
isk managemen s a egies—including es ima ing he scale o necessa y in es men s o
e o i ing, adjus ing s uden - o- olume a ios, o upg ading en ila ion sys ems. Ul i-
ma ely, unde s anding and add essing IAQ- ela ed isks can educe he likelihood o heal h
p oblems, enhance well-being, and imp o e academic pe o mance and quali y o li e
ac oss he educa ional communi y.
2. Fac o s A ec ing Indoo Ai Quali y in Educa ional Cen e s
As an in eg al aspec o he educa ional jou ney, s uden s commonly en ol in elemen-
a y, middle, and high schools, de o ing a subs an ial po ion o hei day o class oom
ins uc ions [
24
]. In es iga ions in o class oom ai quali y and s uden esponses ha e
indica ed a s ong link be ween ai quali y and s uden s’ a en ion p ocesses, wi h high
le els o CO
2
concen a ion leading o educed a en ion span and decision-making abili ies
among s uden s [
25
–
27
]. Beyond in es iga ions conce ning CO
2
concen a ion and i s
e ec s on occupan s’ well-being, indings om se e al esea che s ha e indica ed ha , in
p ac ical e ms, CO
2
concen a ion can se e as a p oxy o IAQ accep abili y [
6
,
9
,
22
,
28
,
29
],
Appl. Sci. 2025,15, 4033 3 o 15
he app op ia eness o ai exchange, and whe he su icien esh ai is being in oduced
in o indoo en i onmen s [28,30].
P io esea ch on CO
2
le els wi hin indoo spaces has highligh ed se e al key ac o s
as in luen ial a iables. These include (1) he CO
2
gene a ion a e; (2) he ou doo CO
2
concen a ions; (3) he olume low a e; (4) he oom dimensions, and (5) he numbe o
occupan s wi hin a gi en space.
While nume ous s udies ha e explo ed CO
2
gene a ion a es in adul s unde a ious
ac i i y le els, he e is limi ed esea ch ocused speci ically on child en and adolescen s
du ing ypical educa ional ac i i ies. Ob aining accu a e CO
2
gene a ion da a o younge
age g oups om exis ing s anda ds o li e a u e can be challenging. Age plays a signi ican
ole in CO
2
p oduc ion, wi h no able sex- ela ed di e ences eme ging a e he age o
15—a which poin boys end o p oduce signi ican ly mo e CO2 han gi ls.
In gene al, CO
2
gene a ion inc eases p opo ionally wi h physical ac i i y le els ac oss all
age g oups. Howe e , due o di e ences in body size and me abolic a es, child en—pa icula ly
hose be ween 5 and 12 yea s o age—consis en ly gene a e less CO
2
han adul s pe o ming
he same ac i i ies [31].
CO
2
emissions om ou doo s sou ces may also ha e immedia e implica ions o he
indoo en i onmen [
32
–
34
], since he ai in bo h na u ally and mechanically en ila ed
buildings is eplenished o a ying deg ees wi h ambien ai , which may o may no be
il e ed o o he wise condi ioned be o e being b ough indoo s.
Al hough ele a ed CO2le els alone migh nega i ely impac s uden s’ ale ness and
concen a ion [
35
], CO
2
is no classi ied as a pollu an by he Wo ld Heal h O ganiza ion.
Indoo ai quali y in schools is nega i ely a ec ed by se e al pollu an s ha a e he esul
o physical, chemical and biological ac o s along wi h he adequacy o en ila ion in he
en i onmen [36].
Aside om he indoo gene a ion a e and ou doo s concen a ions incomes, IAQ
is also in luenced by a mul i ude o addi ional ac o s, such as he size and layou o he
class oom, including i s a ea, olume and ceiling heigh . These ac o s, in u n, ha e a
s ong ela ionship wi h a numbe o occupan s and densi y pe loo a ea and cubic me e ,
ac i i y and exposu e ime, window ype (openable a ea and glazing), he ai igh ness o
he building en elope, exposu e o wind di ec ion, and en ila ion s a egy.
As a esul , IAQ is in luenced by a mul i ude o ac o s, making i s managemen and
con ol c ucial o main aining op imal condi ions. The e o e, in oducing a Simpli ied
Class oom Indoo Ai Quali y Risk Index based on he abo e lis ed ac o s could signi y
p og ess in bo h he design and managemen o educa ional indoo en i onmen s.
3. Me hods: F amewo k o he De ini ion o he Risk Index
Risk is he po en ial o ad e se consequences o impac s due o (1) in e ac ion be-
ween one o mo e na u al o human-induced haza ds, (2) sys ems’ ulne abili ies, and/o
(3) exposu e o humans. Gene ally, he isk is calcula ed as he p oduc o he likelihood o
chance o a speci ic e en o haza d occu ing and he consequences (unde s ood as he
impac s o ou comes) ha esul om such e en o haza d.
Con empo a y unde s anding ecognizes ha isk ex ends beyond me ely gauging he
p obabili y and se e i y o haza dous e en s and hei po en ial consequences. Ins ead, i
eme ges om he in e play o h ee undamen al componen s: (1) haza d; (2) ulne abili y
and (3) exposu e:
•
Haza d— he p ocess, phenomenon, o human ac i i y ha has he po en ial o cause
ha m. In he con ex o his s udy, his e e s o he likelihood o CO
2
concen a ions
exceeding accep able h esholds, based on occupancy, ac i i y le el, and en ila ion
Appl. Sci. 2025,15, 4033 4 o 15
condi ions. Thus, CO
2
concen a ion is indi ec ly conside ed wi hin he haza d com-
ponen o he CIAQ Risk Index.
•
Vulne abili y— he in insic p edisposi ion o a class oom o expe ience nega i e e ec s
due o inadequa e indoo ai quali y (IAQ). This includes a chi ec u al limi a ions,
en ila ion sys em capaci y, and o e all adap abili y o he space.
•
Exposu e— he p esence and du a ion o indi iduals (s uden s and eache s) who may
be a ec ed by a haza dous e en . In ou model, exposu e is es ima ed h ough a isk-
based p oxy, combining he numbe o occupan s (adjus ed o age- ela ed sensi i i y)
and hei ime spen in he class oom aiming a assessing he po en ial in ensi y o
exposu e isk in he absence o di ec measu emen s.
As a esul , he isk ac o associa ed wi h Class oom Indoo Ai Quali y (CIAQ), in
he con ex o his manusc ip , is iden i ied and quan i ied as he p oduc o hose h ee key
elemen s: (1) haza d (H); (2) ulne abili y (V) and (3) exposu e (E). This o mula ion enables
a simpli ied ye in o ma i e e alua ion o IAQ- ela ed isks in educa ional en i onmen s,
suppo ing p oac i e mi iga ion s a egies du ing bo h design and ope a ional phases.
4. Implemen a ion o he Risk Index
4.1. Haza d (H)
The signi icance o ca bon dioxide (
CO2
) le els wi hin IAQ is widely ecognized,
o en se ing as an indica o o en ila ion a es [
11
,
37
]. These CO
2
concen a ions a e
indica i e o IAQ accep abili y and, o his eason, he p e ailing likelihood o exceeding
p ede e mined CO
2
h esholds in a class oom will be he e conside ed as he haza d [
H
]
o he de eloped isk index. No e ha in his case, he H is no in ended o p ecisely
p edic how CO
2
le els will e ol e unde speci ic condi ions and momen bu a he o
iden i y hose class ooms wi h he highes po en ial o CO
2
concen a ion unde he wo s
ci cums ances and bounda y condi ions possible.
Indoo CO
2
le els a e p ima ily in luenced by wo main a iables: (1) he gene a ed
CO
2
wi hin a con ined space [
H1
co2
], and (2) he po en ial in low o ou doo CO
2
con-
cen a ions [
H2
co2
], bo h necessi a ing he conside a ion o se e al ac o s o assess his
haza d (H).
The i s a iable [
H1
co2
] conside s ac o s including (a) he a e a which occupan s
gene a e CO
2
wi hin a con ined space [
COR
2
], based on hei (b) age [
y
] and (c) le el o
ac i i ies [
ac
], and (d) he numbe o po en ial occupan s [
O
]. In his s udy, he a iable [ac]
(exp essed in dimensionless uni s o he me abolic equi alen o ask (me )) ep esen s he
a io o human ene gy expendi u e o a speci ic physical ac i i y o he basal me abolic
a e. Fo e e ence, Table 1p esen s selec ed le els o ac i i y and hei co esponding
gene alized a e age ac alues, based on [
37
]. No e ha hese alues a e no disagg ega ed
by age o sex.
Table 1. Le els o ac i i y and hei co esponding ac alues acco ding o [37].
Desc ip ion o Le el o Ac i i y ac-Le el o Ac i i y (Me )
Res ing o sleeping 0.95
Reclining o si ing calmly 1.0–1.3
S anding s ill o si ing while eading, w i ing, o yping 1.3
Si ing asks wi h minimal exe ion 1.5
S anding asks wi h minimal exe ion (e.g., s o e cle k, iling) 3.0
Walking a a e y slow pace (<2 mph) on a la su ace 2.0
Walking a a mode a e pace (2.8–3.2 mph) on a la su ace 3.5
Ligh o mode a e calis henics 2.8 o 3.8
Mode a e e o cleaning o sweeping 3.8
Dancing—ae obic o gene al 7.8 o 7.3
Appl. Sci. 2025,15, 4033 5 o 15
In o de o acili a e he calcula ion o
H1
co2
, Table 2con ains CO
2
gene a ion a es
[
COR
2
] o a numbe o di e en le els o ac i i y [
ac
] alues o e a ange o ages [
y
]
acco ding o [
37
]. These alues a e mos accu a e, bu s ill inhe en ly app oxima e, when
applied o a g oup o indi iduals and will no gene ally be accu a e o a single indi idual.
Using he
COR
2
gene a ion a e alues, he Gene a ion Ra e Index [
ICOR
2
] is di ec ly e ie ed
by escaling he la e and mul iplying i by 12.5.
Table 2. Ra e a which occupan s gene a e
CO2
wi hin a con ined space [
COR
2
] and i s co esponding
Gene a ed CO2Index [ICO2].
Age
(y)
ac-Le el o Ac i i y (Me ) ac-Le el o Ac i i y (Me )
1.0 1.2 1.4 1.6 2.0 3.0 4.0 1.0 1.2 1.4 1.6 2.0 3.0 4.0
COR
2(L/s) ICOR
2(-)
<1
0.0009 0.0011 0.0013 0.0014 0.0018 0.0027 0.0036
0.011 0.014 0.016 0.018 0.023 0.034 0.045
1 o <3
0.0015 0.0018 0.0021 0.0024
0.003
0.0044 0.0059
0.019 0.023 0.026 0.030 0.038 0.055 0.074
3 o <6
0.0019 0.0023 0.0026
0.003
0.0038 0.0057 0.0075
0.024 0.029 0.033 0.038 0.048 0.071 0.094
6 o <11
0.0025
0.003
0.0035
0.004 0.005
0.0075
0.01 0.031 0.038 0.044 0.050 0.063 0.094 0.125
11 o <16
0.0034 0.0041 0.0048 0.0054 0.0068 0.0102 0.0136
0.043 0.051 0.060 0.068 0.085 0.128 0.170
16 o <21
0.0037 0.0045 0.0053
0.006
0.0075 0.0113
0.015 0.046 0.056 0.066 0.075 0.094 0.141 0.188
21 o <30
0.0039 0.0048 0.0056 0.0064
0.008 0.012 0.016 0.049 0.060 0.070 0.080 0.100 0.150 0.200
30 o <40
0.0037 0.0046 0.0053 0.0061 0.0076 0.0114 0.0152
0.046 0.058 0.066 0.076 0.095 0.143 0.190
Figu e 1plo s he alues o he o
COR
2
(Figu e 1a) and
ICOR
2
(Figu e 1b) o di e en
ac
alues and y anges conside ed in his manusc ip .
Appl. Sci. 2025, 15, x FOR PEER REVIEW 5 o 15
Table 1. Le els o ac i i y and hei co esponding ac alues acco ding o [37].
Desc ip ion o Le el o Ac i i y 𝒂𝒄-Le el o Ac i i y (Me )
Res ing o sleeping 0.95
Reclining o si ing calmly 1.0–1.3
S anding s ill o si ing while eading, w i ing, o yping 1.3
Si ing asks wi h minimal exe ion 1.5
S anding asks wi h minimal exe ion (e.g., s o e cle k, iling) 3.0
Walking a a e y slow pace (<2 mph) on a la su ace 2.0
Walking a a mode a e pace (2.8–3.2 mph) on a la su ace 3.5
Ligh o mode a e calis henics 2.8 o 3.8
Mode a e e o cleaning o sweeping 3.8
Dancing—ae obic o gene al 7.8 o 7.3
Table 2. Ra e a which occupan s gene a e CO
wi hin a con ined space [CO
] and i s co esponding
Gene a ed CO
Index [I
].
Age
(y)
𝒂𝒄-Le el o Ac i i y (
M
e ) 𝒂𝒄-Le el o Ac i i y (
M
e )
1.0 1.2 1.4 1.6 2.0 3.0 4.0 1.0 1.2 1.4 1.6 2.0 3.0 4.0
𝑪𝑶
𝟐
𝑹
(L/s) 𝑰
𝑪𝑶
𝟐
𝑹
(-)
<1 0.0009 0.0011 0.0013 0.0014 0.0018 0.0027 0.0036 0.011 0.014 0.016 0.018 0.023 0.034 0.045
1 o <3 0.0015 0.0018 0.0021 0.0024 0.003 0.0044 0.0059 0.019 0.023 0.026 0.030 0.038 0.055 0.074
3 o <6 0.0019 0.0023 0.0026 0.003 0.0038 0.0057 0.0075 0.024 0.029 0.033 0.038 0.048 0.071 0.094
6 o <11 0.0025 0.003 0.0035 0.004 0.005 0.0075 0.01 0.031 0.038 0.044 0.050 0.063 0.094 0.125
11 o <16 0.0034 0.0041 0.0048 0.0054 0.0068 0.0102 0.0136 0.043 0.051 0.060 0.068 0.085 0.128 0.170
16 o <21 0.0037 0.0045 0.0053 0.006 0.0075 0.0113 0.015 0.046 0.056 0.066 0.075 0.094 0.141 0.188
21 o <30 0.0039 0.0048 0.0056 0.0064 0.008 0.012 0.016 0.049 0.060 0.070 0.080 0.100 0.150 0.200
30 o <40 0.0037 0.0046 0.0053 0.0061 0.0076 0.0114 0.0152 0.046 0.058 0.066 0.076 0.095 0.143 0.190
Figu e 1 plo s he alues o he o CO
(Figu e 1a) and I
(Figu e 1b) o di e en
ac alues and y anges conside ed in his manusc ip .
Figu e 1. (a) Values o CO
and (b) I
o di e en ac and y anges conside ed.
Based on hese alues and o quali a i ely assess he impac o H
in H, Equa ion
(1) was de eloped. This equa ion ends o alloca e highe and lowe alues o scena ios
wi h inc eased and educed isk, espec i ely, abs aining om embodying a pa icula
physical implica ion, by mul iplying he occupancy [O] by he p e iously de ined Gene -
a ion Ra e Index [I
].
Hco2
1
O
y
,ac
ICO
2
R
(1)
Ou doo ai quali y CO alues may no di ec ly a ec indoo CO concen a ions,
bu i s impac on building en ila ion a es, occupan beha io s, and indoo ai quali y
managemen s a egies can indi ec ly in luence indoo CO le els. CO le els in ou doo
0
0.005
0.01
0.015
0.02
01234
CO2 gene a ed a e (L/s)
Le el o ac i i y [ac] (me )
<1 yea
1 o < 3 yea s
3 o < 6 yea s
6 o < 11 yea s
11 o < 16 yea s
16 o < 21 yea s
21 o < 30 yea s
30 o < 40 yea s
0
0.05
0.1
0.15
0.2
0.25
01234
Gene a ion a e Index (-)
Le el o ac i i y [ac] (me )
<1 yea
1 o < 3 yea s
3 o < 6 yea s
6 o < 11 yea s
11 o < 16 yea s
16 o < 21 yea s
21 o < 30 yea s
30 o < 40 yea s
(a) (b)
Figu e 1. (a) Values o COR
2and (b) ICOR
2 o di e en ac and y anges conside ed.
Based on hese alues and o quali a i ely assess he impac o
H1
co2
in
H
, Equa ion (1)
was de eloped. This equa ion ends o alloca e highe and lowe alues o scena ios wi h
inc eased and educed isk, espec i ely, abs aining om embodying a pa icula physical
implica ion, by mul iplying he occupancy [
O
] by he p e iously de ined Gene a ion Ra e
Index [ICOR
2].
H1
co2 =∑ ∑ Oy,acICOR
2(1)
Ou doo ai quali y
CO2
alues may no di ec ly a ec indoo
CO2
concen a ions,
bu i s impac on building en ila ion a es, occupan beha io s, and indoo ai quali y
managemen s a egies can indi ec ly in luence indoo
CO2
le els.
CO2
le els in ou doo
ai gene ally all be ween 300 and 400 ppm bu may be ele a ed in u ban a eas, pa icula ly
nea busy oads. Fo his eason, he second a iable [
H2
co2
] conside ed in he calcula ion o
H
is linked o he mic oen i onmen and encompasses conside a ions such as geog aphical
loca ion [L] and p oximi y o a ic. In o de o conside hose ci cums ances in he
H
Appl. Sci. 2025,15, 4033 6 o 15
calcula ion, Table 3p o ides he alues o he a iable [
H2
co2
] depending on he loca ion
and p oximi y o a ic o he class oom being assessed.
Table 3. Values o he a iable [
H2
co2
] depending on he loca ion and p oximi y o a ic o he
class oom being assessed.
Loca ion and P oximi y o T a ic Ca ego y H2
co2
U ban loca ion in immedia e p oximi y o high a ic s ee L5 1.10
U ban backg ound L4 1.07
Residen ial loca ion wi h a high s ee less han 400 m away L3 1.05
Residen ial loca ion wi h a high s ee mo e han 400 m away
L2 1.02
Subu ban o u al L1 1.00
Conside ing he abo e-men ioned in o ma ion, he calcula ion o
H
(Equa ion (2)) is
he esul o mul iplying he haza d associa ed wi h he gene a ed
CO2
wi hin a con ined
space [
H1
co2
], by he ac o conside ing he po en ial in low o ou doo
CO2
concen a ions
[
H2
co2
]. Reade s should bea in mind ha he equa ion aims o assign highe alues o
si ua ions o g ea e haza ds and lowe alues o lesse haza ds, ye i does no in end o
ep esen a speci ic physical signi icance.
H=H1
co2 ×H2
co2 (2)
As an example, Figu e 2illus a es he
H
wi hin an imagina y subu ban class oom,
conside ing a ious numbe s o occupan s [
O
]. Two scena ios a e depic ed: one wi h a
ixed le el o ac i i y [ac] o 1.6 me (Figu e 2a) and ano he wi h a ixed age [
y
] o 12 yea s
(Figu e 2b). These scena ios encompass di e en ac alues and age anges as ou lined in
his manusc ip .
Figu e 2. Values o he H o (a) ixed ac o 1.6 me and (b) ixed y o 12 yea s.
4.2. Vulne abili y (V)
Assessing he ulne abili y o an asse (in his case, a class oom) is c ucial o in o ming
decisions and shaping policies o u u e adjus men s, as i helps se p io i ies ha in luence
he class oom’s a chi ec u e and design. In his ega d, he ulne abili y alue aims o
measu e he capaci y o he class oom, unde s ood as an a chi ec u al space wi h i s design
and ins alla ion limi a ions, o main ain good indoo ai quali y. Thus, he size o he
class oom along wi h he e ec i eness o he en ila ion sys em a e he main ac o s he e
conside ed o quali a i ely assess he class oom ulne abili y. To assess such e ec i eness,
he concep o ai changes pe hou (ACH) will be he e used. ACH e e s o he numbe
o imes pe hou ha he o al ai olume wi hin a speci ic space is eplaced; in his
case, a ce ain class oom is eplaced wi h supply and/o eci cula ed ai (using na u al,
Appl. Sci. 2025,15, 4033 7 o 15
mechanical o hyb id means). Consequen ly, ac o s such as he occupancy, olume and
ai low en ila ion a io a e he e conside ed.
In his ega d, he EN 16798-3 s anda d [
38
] o en ila ion in non- esiden ial buildings
iden i ies ou ai quali y ca ego ies (1: op imum, 2: good, 3: medium and 4: low) wi h ou -
doo ai low a es [in dm
3
/s pe occupan ] o 20.0, 12.5, 8.0 and 5.0, espec i ely [
38
]. Fo
spaces dedica ed o eaching and lea ning, he Spanish Regula ion on Building Hea ing In-
s alla ions (RITE) equi es a minimum Ca ego y 2 [
39
]. In Po ugal, na ional egula ions [
40
]
es ablish a minimum ou doo ai low a e o 24 m
3
/(h
·
occupan ) o eaching/lea ning
spaces, alling be ween Ca ego y 3 and Ca ego y 4 o [38].
Based on such alues, Equa ion (3) was designed in o de o assign a ulne abili y
ac o acco ding o class oom en ila ion capaci y de ined as ACH alues. This ela ionship,
shown in Figu e 3, assigns a maximum sco e o 10 poin s when ACH is ze o and dec eases
linea ly o 0 when ACH eaches 10. Likewise, highe ACH alues a e also associa ed wi h
he absence o ulne abili y.
V=(10 −ACH o 0≤ACH ≤10
0ACH >10 (3)
Appl. Sci. 2025, 15, x FOR PEER REVIEW 7 o 15
he e conside ed o quali a i ely assess he class oom ulne abili y. To assess such e ec-
i eness, he concep o ai changes pe hou (ACH) will be he e used. ACH e e s o he
numbe o imes pe hou ha he o al ai olume wi hin a speci ic space is eplaced; in
his case, a ce ain class oom is eplaced wi h supply and/o eci cula ed ai (using na u-
al, mechanical o hyb id means). Consequen ly, ac o s such as he occupancy, olume
and ai low en ila ion a io a e he e conside ed.
In his ega d, he EN 16798-3 s anda d [38] o en ila ion in non- esiden ial build-
ings iden i ies ou ai quali y ca ego ies (1: op imum, 2: good, 3: medium and 4: low) wi h
ou doo ai low a es [in dm
3
/s pe occupan ] o 20.0, 12.5, 8.0 and 5.0, espec i ely [38].
Fo spaces dedica ed o eaching and lea ning, he Spanish Regula ion on Building Hea -
ing Ins alla ions (RITE) equi es a minimum Ca ego y 2 [39]. In Po ugal, na ional egula-
ions [40] es ablish a minimum ou doo ai low a e o 24 m
3
/(h·occupan ) o each-
ing/lea ning spaces, alling be ween Ca ego y 3 and Ca ego y 4 o [38].
Based on such alues, Equa ion (3) was designed in o de o assign a ulne abili y
ac o acco ding o class oom en ila ion capaci y de ined as ACH alues. This ela ion-
ship, shown in Figu e 3, assigns a maximum sco e o 10 poin s when ACH is ze o and
dec eases linea ly o 0 when ACH eaches 10. Likewise, highe ACH alues a e also asso-
cia ed wi h he absence o ulne abili y.
𝑉
10
𝐴
𝐶𝐻
𝑓
𝑜𝑟 0
𝐴
𝐶𝐻 10
0
𝐴
𝐶𝐻 10 (3)
Figu e 3. Rela ionship designed o assign a ulne abili y ac o acco ding o class oom en ila ion
capaci y de ined as ACH alues.
I should be poin ed ou ha he possible en ila ion con igu a ions ha can be im-
plemen ed in each class oom (na u al c oss en ila ion—wi h windows and/o doo s, sin-
gle-sided en ila ion, mechanically en ila ed o hyb id en ila ion) depend on i s cha -
ac e is ics and, hence, he en ila ion a e (VR) ha is possible o achie e wi h hese s a -
egies is condi ioned by he class oom design. In he case o spaces ha a e mechanically
en ila ed, educing ai eci cula ion and inc easing he VR a e sugges ed [41]. Howe e ,
mos educa ional buildings in Eu ope do no ha e mechanical en ila ion sys ems [11].
The e o e, since he en ila ion sys em de e mines he s a egies ha can be implemen ed
o con ol o inc ease he ai enewal a e, he la e can only be achie ed h ough na u al
en ila ion. In his sense, di e en au ho s ha e aised ha c oss-na u al en ila ion con-
igu a ions gene ally p o ide mo e e ec i e ai eno a ion han he single-side en ila-
ion con igu a ion [42–44]. As a e e ence alue, Aguila e al. [11] ob ained alues be-
ween 2.9 and 20.1 ACH o na u al c oss en ila ion, 2.0 o 5.1 ACH o single-sided en-
ila ion, and 1.8 o 3.5 o mechanically en ila ed class ooms.
The app oach o na u al en ila ion used du ing class oom ac i i ies plays a c ucial
ole in shaping bo h he mal and acous ic com o . I is essen ial o main ain a sa e and
0
2
4
6
8
10
0 2.5 5 7.5 10 12.5 15
Vulne abili y [V]
ACH
Figu e 3. Rela ionship designed o assign a ulne abili y ac o acco ding o class oom en ila ion
capaci y de ined as ACH alues.
I should be poin ed ou ha he possible en ila ion con igu a ions ha can be im-
plemen ed in each class oom (na u al c oss en ila ion—wi h windows and/o doo s,
single-sided en ila ion, mechanically en ila ed o hyb id en ila ion) depend on i s
cha ac e is ics and, hence, he en ila ion a e (VR) ha is possible o achie e wi h hese
s a egies is condi ioned by he class oom design. In he case o spaces ha a e mechanically
en ila ed, educing ai eci cula ion and inc easing he VR a e sugges ed [
41
]. Howe e ,
mos educa ional buildings in Eu ope do no ha e mechanical en ila ion sys ems [
11
].
The e o e, since he en ila ion sys em de e mines he s a egies ha can be implemen ed
o con ol o inc ease he ai enewal a e, he la e can only be achie ed h ough na u al
en ila ion. In his sense, di e en au ho s ha e aised ha c oss-na u al en ila ion con ig-
u a ions gene ally p o ide mo e e ec i e ai eno a ion han he single-side en ila ion
con igu a ion [
42
–
44
]. As a e e ence alue, Aguila e al. [
11
] ob ained alues be ween 2.9
and 20.1 ACH o na u al c oss en ila ion, 2.0 o 5.1 ACH o single-sided en ila ion, and
1.8 o 3.5 o mechanically en ila ed class ooms.
The app oach o na u al en ila ion used du ing class oom ac i i ies plays a c ucial
ole in shaping bo h he mal and acous ic com o . I is essen ial o main ain a sa e and
heal hy indoo en i onmen while also implemen ing s a egies ha p ese e ai quali y
wi hou comp omising o he indoo en i onmen al ac o s.
Appl. Sci. 2025,15, 4033 8 o 15
4.3. Exposu e (E)
In he cons uc ion o he exposu e index o educa ional en i onmen s, ca e ul con-
side a ion will be gi en o he numbe o occupan s in he class oom. Recognizing ha
younge s uden s a e mo e sensi i e and equi e inc eased p o ec ion agains poo ai
quali y, he calcula ion will emphasize hei signi icance. An illus a i e example is ha
in a class oom occupied by he minimum numbe
[O]
o s uden s, he
hO*i
o equi alen
occupancy will be highe when he s uden s a e younge . This unde sco es he heigh ened
impo ance o younge s uden s in de e mining he o e all exposu e index.
Addi ionally, he exposu e index will conside he du a ion o exposu e [
T
]. The longe
he ime spen in he class oom, he g ea e he po en ial impac on occupan s. Consid-
e ing bo h he numbe o occupan s (a ec ed by he sensi i i y index, [
y
] acco ding o
Table 4) and he du a ion o exposu e, he exposu e index aims o p o ide a comp ehensi e
assessmen o he po en ial isks in he gi en en i onmen (Equa ion (4)). This app oach
ensu es a mo e de ailed and p o ec i e e alua ion, pa icula ly o he mo e ulne able and
sensi i e younge s uden s. Figu e 4shows he ela ion be ween he numbe o s uden s
and he co esponden equi alen occupancy o di e en ages o s uden s.
E=(O∗)×T=O× y×T(4)
Table 4. Age o child en/adolescen s and he co esponding sensi i i y index [
y
] adop ed o he
calcula ion o exposu e index.
Age o Child en/Adolescen s Sensi i i y Index ( y)
In an school: ages 0 o 6 1.25
P ima y educa ion: ages 6 o 12 1.15
Obliga o y seconda y educa ion: ages 12 o 16 1.10
Uni e si y p epa a ion o oca ional aining: ages 15 o 18
1.05
Uni e si y 1.00
Appl. Sci. 2025, 15, x FOR PEER REVIEW 8 o 15
heal hy indoo en i onmen while also implemen ing s a egies ha p ese e ai quali y
wi hou comp omising o he indoo en i onmen al ac o s.
4.3. Exposu e (E)
In he cons uc ion o he exposu e index o educa ional en i onmen s, ca e ul con-
side a ion will be gi en o he numbe o occupan s in he class oom. Recognizing ha
younge s uden s a e mo e sensi i e and equi e inc eased p o ec ion agains poo ai
quali y, he calcula ion will emphasize hei signi icance. An illus a i e example is ha
in a class oom occupied by he minimum numbe O o s uden s, he O∗ o equi alen
occupancy will be highe when he s uden s a e younge . This unde sco es he heigh ened
impo ance o younge s uden s in de e mining he o e all exposu e index.
Addi ionally, he exposu e index will conside he du a ion o exposu e [T]. The
longe he ime spen in he class oom, he g ea e he po en ial impac on occupan s. Con-
side ing bo h he numbe o occupan s (a ec ed by he sensi i i y index, [
y
]
acco ding o
Table 4) and he du a ion o exposu e, he exposu e index aims o p o ide a comp ehen-
si e assessmen o he po en ial isks in he gi en en i onmen (Equa ion (4)). This ap-
p oach ensu es a mo e de ailed and p o ec i e e alua ion, pa icula ly o he mo e ul-
ne able and sensi i e younge s uden s. Figu e 4 shows he ela ion be ween he numbe
o s uden s and he co esponden equi alen occupancy o di e en ages o s uden s.
𝐸𝑂∗𝑇𝑂
𝑓
𝑇 (4)
Table 4. Age o child en/adolescen s and he co esponding sensi i i y index [
y
]
adop ed o he
calcula ion o exposu e index.
Age o Child en/Adolescen s Sensi i i y Index (
y
)
In an school: ages 0 o 6 1.25
P ima y educa ion: ages 6 o 12 1.15
Obliga o y seconda y educa ion: ages 12 o 16 1.10
Uni e si y p epa a ion o oca ional aining: ages 15 o 18 1.05
Uni e si y 1.00
Figu e 4. (a) Rela ion be ween O and O* o di e en ages and (b) de ailed o an occupancy ange
o 15–30.
5. S udy Cases
5.1. De ini ion o he Cases
The p oposed CIAQ Risk Index was implemen ed using a case s udy based on a
benchma k class oom model, cha ac e ized by ypical condi ions commonly ound in
Spanish educa ional buildings (see Figu e 5).
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30
Eq. Occupancy [O*]
Occupancy [O]
5 yea s
9 yea s
15 yea s
17 yea s
21 yea s
15
20
25
30
35
40
15 20 25 30
Eq. Occupancy [O*]
Occupancy [O]
5 yea s
9 yea s
15 yea s
17 yea s
21 yea s
(a) (b)
Figu e 4. (a) Rela ion be ween O and O* o di e en ages and (b) de ailed o an occupancy ange o
15–30.
5. S udy Cases
5.1. De ini ion o he Cases
The p oposed CIAQ Risk Index was implemen ed using a case s udy based on a
benchma k class oom model, cha ac e ized by ypical condi ions commonly ound in
Spanish educa ional buildings (see Figu e 5).
Appl. Sci. 2025,15, 4033 9 o 15
Appl. Sci. 2025, 15, x FOR PEER REVIEW 9 o 15
Figu e 5. Benchma k class oom model used in he case s udy.
This e e ence case is de ined by se en key pa ame e s: (1) class oom olume (in m³),
(2) age o child en/adolescen s (yea s), (3) maximum occupancy o he class oom (numbe
o s uden s), (4) ac i i y le el (me ), (5) loca ion and p oximi y o a ic (p e iously es ab-
lished ca ego ies, see Sec ion 4.1), (6) en ila ion sys em (as olume ic ai low in li e s pe
second), and (7) du a ion o exposu e (hou s). The adop ed baseline alues (Table 5) we e
selec ed o ep esen a e age o s anda d class oom condi ions in Spain.
Table 5. De ini ion o he 16 case s udies analyzed.
CODE
Ven ila ion Sys-
em
[Ven]
Loca ion and P ox-
imi y o T a ic
Ac i i y
Le el
[𝒂𝒄]
Maximum Oc-
cupancy
[𝑶]
Class oom Vol-
ume
[Vol]
Age
[y]
Du a ion o Expo-
su e
[T]
CL-X1 190 L3 1,3 25 170 10 2h
CL-A2 190 L3 1,3 25 170 10 1 h
CL-A3 190 L3 1,3 25 170 10 3 h
CL-B2 190 L3 1,3 25 170 5 2 h
CL-B3 190 L3 1,3 25 170 15 2 h
CL-C2 190 L3 1,3 25 120 10 2 h
CL-C3 190 L3 1,3 25 220 10 2 h
CL-D2 190 L3 1,3 20 170 10 2 h
CL-D3 190 L3 1,3 30 170 10 2 h
CL-E2 190 L3 1,0 25 170 10 2 h
CL-E3 190 L3 3,0 25 170 10 2 h
CL-F2 190 L1 1,3 25 170 10 2 h
CL-F3 190 L5 1,3 25 170 10 2 h
CL-G2 45 L3 1,3 25 170 10 2 h
CL-G3 330 L3 1,3 25 170 10 2 h
Impo an ly, his case s udy— e e ed o as CL-X1 in Table 5—se ed as he basis o
a sensi i i y analysis, in which one pa ame e a a ime was modi ied while he o he s
emained ixed. Each a ia ion ep esen s a simula ed scena io a he han a physical
class oom, allowing o he sys ema ic e alua ion o how indi idual a iables in luence
he o e all CIAQ Risk Index. This app oach o e s a con olled and eplicable me hod o
assess he ela i e impo ance o di e en ac o s, suppo ing mo e in o med decision-
making in he design, eno a ion, o ope a ional planning o educa ional spaces.
In his ega d, he du a ion o he exposu e (CL-A) and he age o he child en/ado-
lescen s (CL-B) we e inc eased/ educed by 50%; he ob ained anges co e he ypical du-
a ion o he sessions and he ages ha a e mo e sensi i e o poo ai quali y (Sec ion 4.3).
The magni udes ela ed o he class oom olume (CL-C) and maximum occupancy (CL-
D) a ied o a lesse ex en : he a ia ions o 30% and 20% we e assumed, espec i ely.
The e e ence (case) s udy conside ed he ac i i y le el o 1.3 ha ep esen s he mos
common ac i i ies wi hin he educa ion p ocess, i.e., si ing eading, w i ing, and yping.
Figu e 5. Benchma k class oom model used in he case s udy.
This e e ence case is de ined by se en key pa ame e s: (1) class oom olume (in
m
3
), (2) age o child en/adolescen s (yea s), (3) maximum occupancy o he class oom
(numbe o s uden s), (4) ac i i y le el (me ), (5) loca ion and p oximi y o a ic (p e iously
es ablished ca ego ies, see Sec ion 4.1), (6) en ila ion sys em (as olume ic ai low in li e s
pe second), and (7) du a ion o exposu e (hou s). The adop ed baseline alues (Table 5)
we e selec ed o ep esen a e age o s anda d class oom condi ions in Spain.
Table 5. De ini ion o he 16 case s udies analyzed.
CODE
Ven ila ion
Sys em
[Ven]
Loca ion and
P oximi y o
T a ic
Ac i i y
Le el
[ac]
Maximum
Occupancy
[O]
Class oom
Volume
[Vol]
Age
[y]
Du a ion o
Exposu e
[T]
CL-X1 190 L3 1,3 25 170 10 2h
CL-A2 190 L3 1,3 25 170 10 1 h
CL-A3 190 L3 1,3 25 170 10 3 h
CL-B2 190 L3 1,3 25 170 5 2 h
CL-B3 190 L3 1,3 25 170 15 2 h
CL-C2 190 L3 1,3 25 120 10 2 h
CL-C3 190 L3 1,3 25 220 10 2 h
CL-D2 190 L3 1,3 20 170 10 2 h
CL-D3 190 L3 1,3 30 170 10 2 h
CL-E2 190 L3 1,0 25 170 10 2 h
CL-E3 190 L3 3,0 25 170 10 2 h
CL-F2 190 L1 1,3 25 170 10 2 h
CL-F3 190 L5 1,3 25 170 10 2 h
CL-G2 45 L3 1,3 25 170 10 2 h
CL-G3 330 L3 1,3 25 170 10 2 h
Impo an ly, his case s udy— e e ed o as CL-X1 in Table 5—se ed as he basis o
a sensi i i y analysis, in which one pa ame e a a ime was modi ied while he o he s
emained ixed. Each a ia ion ep esen s a simula ed scena io a he han a physical
class oom, allowing o he sys ema ic e alua ion o how indi idual a iables in luence he
o e all CIAQ Risk Index. This app oach o e s a con olled and eplicable me hod o assess
he ela i e impo ance o di e en ac o s, suppo ing mo e in o med decision-making in
he design, eno a ion, o ope a ional planning o educa ional spaces.
In his ega d, he du a ion o he exposu e (CL-A) and he age o he child en/
adolescen s (CL-B) we e inc eased/ educed by 50%; he ob ained anges co e he ypical
du a ion o he sessions and he ages ha a e mo e sensi i e o poo ai quali y (Sec ion 4.3).
The magni udes ela ed o he class oom olume (CL-C) and maximum occupancy (CL-D)
a ied o a lesse ex en : he a ia ions o 30% and 20% we e assumed, espec i ely.
