Assessment of climate resilience in vulnerable buildings in the city of Barcelona

Bachelo ’s Thesis
Bachelo ’s Deg ee in Indus ial Technologies
Assessmen o clima e esilience in
ulne able buildings in he ci y o
Ba celona
REPORT
Au ho : Ma ia Cano Teixidó
Supe iso : Rose Capde ila Pa amio
Call: Janua y 2025
Escola Tècnica Supe io
d’Enginye ia Indus ial de Ba celona
Pàg. 2 Memò ia
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 3
Resum
Aques a esi anali za la esiliència i el con o è mic de l’edi ici ipus més ep esen a iu del
ba i amb meno enda de Ba celona, ubica en una zona amb clima medi e ani
con inen al. L’objec iu p incipal és examina com espon un habi a ge conside a ulne able
i poc p epa a da an l’inc emen de les empe a u es i al es enòmens ex ems incula s
al can i climà ic. La selecció de l’edi ici ha es a ui d’un p océs p e i de ece ca acu ada
sob e quins indicado s de pob esa ene gè ica poden u ili za -se a escala de ba i. To i que
mol s d’aques s indicado s eque eixen dades especí iques di ícilmen accessibles com a
es udian , es a iden i ica que la enda mi jana disponible és una a iable ecu en en la
majo ia d’ells i, a més, accessible públicamen . Pe aques mo iu, es a op a pe e se i
aques indicado com a base pe ia el ba i amb meno enda mi jana de Ba celona. Un
cop selecciona , es an es udia les ipologies cons uc i es p edominan s i es a escolli
l’edi ici més ep esen a iu, jun amen amb els ma e ials que el componen.
L’es udi inco po a ecnologies de e ige ació assequibles pe a amílies amb baixos
ing essos, p io i zan l’ús d’es a ègies passi es, aplicades a un model d’edi ici
desen olupa mi jançan les pla a o mes OpenS udio i Ene gyPlus. Les dades climà iques
emp ades han es a gene ades seguin la me odologia de l’Annex 80 pe a la ciu a de
Ba celona, en is a del pi jo escena i p e is de l’IPCC, la ia RCP8.5. S’han conside a
es escena is empo als: el p esen (2006-2025), el u u a mi jà e mini (2041-2060) i el
u u a lla g e mini (2081-100), amb un en ocamen especial en les onades de calo
ex emes. Pe a alua la espos a de l’edi ici, s’han u ili za di e sos indicado s de con o i
esiliència.
Pe a alua la espos a de l’edi ici, s’han u ili za di e sos indicado s de con o i esiliència.
A més, s’ha du a e me una anàlisi d’es udis simila s cen a s en els e ec es del can i
climà ic sob e edi icis en si uació de ulne abili a econòmica, amb l’objec iu d’iden i ica
nous indicado s ú ils i àcilmen aplicables en u u es in es igacions. A més, s’ha eali za
un anàlisi d’es udis simila s cen a s en els e ec es del can i climà ic sob e edi icis en
si uació de ulne abili a econòmica, amb l’objec iu d’iden i ica nous indicado s que puguin
se ú ils i àcilmen aplicables en u u s eballs. Els esul a s ob ingu s olen con ibui a la
de ecció i mi igació de la pob esa ene gè ica, des acan com aques a po eu e’s ag eujada
pels e ec es del can i climà ic. To i que les es a ègies passi es man enen una ce a
e icàcia en l’escena i ac ual, el seu endimen disminueix conside ablemen en els
escena is u u s, posan en isc la salu dels ocupan s. Aques e posa de mani es la
necessi a d’inco po a solucions híb ides o ac i es de baix cos . Malg a les limi acions
p òpies dels p og ames de simulació i la ince esa associada a les p ojeccions climà iques,
aques es udi p e én assen a les bases pe a u u s anàlisis ene gè ics més comple s,
enin en comp e a demés la pa socioeconòmica, en què els indicado s de pob esa se an
de g an ajuda.
Pàg. 4 Memò ia
Resumen
Es a esis analiza la esiliencia y el con o é mico del edi icio ipo más ep esen a i o del
ba io con meno en a de Ba celona, si uado en una zona de clima medi e áneo
con inen al. El obje i o p incipal es examina cómo esponde una i ienda conside ada
ulne able y poco p epa ada an e el aumen o de las empe a u as y o os enómenos
ex emos elacionados con el cambio climá ico. La selección del edi icio ha sido u o de un
p oceso p e io de in es igación igu osa sob e qué indicado es de pob eza ene gé ica
pueden aplica se a escala de ba io. Aunque muchos de es os indicado es equie en da os
especí icos que esul an inaccesibles como es udian e, se iden i icó que la en a media
disponible es una a iable ecu en e en la mayo ía de ellos y, además, es á disponible
públicamen e. Po ello, se eligió es e indicado como base pa a selecciona el ba io con
meno en a media de Ba celona. Una ez seleccionado, se es udia on las ipologías
cons uc i as p edominan es y se escogió el edi icio más ep esen a i o, jun o con los
ma e iales que lo componen.
El es udio inco po a ecnologías de e ige ación asequibles pa a amilias con bajos
ing esos, p io izando el uso de es a egias pasi as, aplicadas a un modelo de edi icio
desa ollado con las pla a o mas OpenS udio y Ene gyPlus. Los da os climá icos u ilizados
han sido gene ados siguiendo la me odología del Annex 80 pa a la ciudad de Ba celona,
en is a del peo escena io espe ado po el IPCC, la ía RCP8.5. Se han conside ado es
escena ios empo ales: p esen e (2006-2025), u u o a medio plazo (2041-2060) y u u o a
la go plazo (2081-2100), con especial a ención a los episodios de olas de calo ex ema.
Pa a e alua la espues a del edi icio se han empleado di e sos indicado es de con o y
esiliencia. Además, se ha ealizado un análisis de es udios simila es cen ados en los
e ec os del cambio climá ico sob e edi icios en si uación de ulne abilidad económica, con
el obje i o de iden i ica nue os indicado es ú iles y ácilmen e aplicables en u u as
in es igaciones.
Además, se ha ealizado un análisis de es udios simila es cen ados en los e ec os del
cambio climá ico sob e edi icios en si uación de ulne abilidad económica, con el obje i o
de iden i ica nue os indicado es que puedan se ú iles y ácilmen e aplicables en u u os
abajos. Los esul ados ob enidos buscan con ibui a la de ección y mi igación de la
pob eza ene gé ica, des acando cómo es a puede e se ag a ada po los e ec os del
cambio climá ico. Aunque las es a egias pasi as man ienen cie a e icacia en el escena io
ac ual, su endimien o disminuye conside ablemen e en escena ios u u os, poniendo en
iesgo la salud de los ocupan es. Es e hecho pone de mani ies o la necesidad de inco po a
soluciones híb idas o ac i as de bajo cos e. A pesa de las limi aciones p opias de los
p og amas de simulación y la ince idumb e asociada a las p oyecciones climá icas, es e
es udio p e ende sen a las bases pa a u u os análisis ene gé icos más comple os,
eniendo en cuen a además la dimensión socioeconómica, en la que los indicado es de
pob eza se án de g an u ilidad.
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 5
Abs ac
This hesis analyses he esilience and he mal com o o he mos ep esen a i e building
ype in he lowes -income neighbou hood o Ba celona, loca ed in a egion wi h a
con inen al Medi e anean clima e. The main objec i e is o examine how a ulne able and
poo ly adap ed dwelling esponds o ising empe a u es and o he ex eme wea he e en s
associa ed wi h clima e change. The selec ion o he building was he esul o a ho ough
p elimina y in es iga ion in o which ene gy po e y indica o s can be applied a he
neighbou hood scale. While many o hese indica o s equi e speci ic da a ha a e no
easily accessible o s uden s, a e age disposable income was iden i ied as a ecu ing and
publicly a ailable a iable in mos o hem. Consequen ly, his indica o was used o selec
he neighbou hood wi h he lowes a e age income in Ba celona. Once i was selec ed, he
p edominan building ypologies we e s udied, and he mos ep esen a i e s uc u e, along
wi h i s cons uc ion ma e ials, was chosen.
The s udy inco po a es cooling echnologies a o dable o low-income households, wi h a
ocus on passi e s a egies applied o a building model de eloped using OpenS udio and
Ene gyPlus pla o ms. The clima e da a used in he simula ions we e gene a ed ollowing
he me hodology p oposed by Annex 80 o he ci y o Ba celona, gi en he wo s expec ed
IPCC scena io, he RCP8.5 pa hway. Th ee empo al scena ios we e conside ed: p esen
day (2006-2025), mid- e m u u e (2041-2060), and long- e m u u e (2081-2100), wi h
special a en ion gi en o ex eme hea wa e e en s.
To assess he building's pe o mance, se e al indica o s o he mal com o and esilience
we e used. Addi ionally, a li e a u e e iew o simila s udies was conduc ed, ocusing on
he impac o clima e change on economically ulne able buildings, aiming o iden i y new,
p ac ical, and applicable indica o s o u u e wo k.
Addi ionally, an analysis o simila s udies ocusing on he e ec s o clima e change on
buildings in si ua ions o economic ulne abili y has been ca ied ou , wi h he aim o
iden i ying new indica o s ha could be use ul and easily applicable in u u e wo k. The
esul s ob ained seek o con ibu e o he de ec ion and mi iga ion o ene gy po e y,
highligh ing how i may be exace ba ed by he e ec s o clima e change. Al hough passi e
s a egies e ain a ce ain deg ee o e ec i eness unde cu en condi ions, hei
pe o mance declines signi ican ly in u u e scena ios, posing a isk o he heal h o
occupan s. This si ua ion highligh s he need o inco po a e low-cos hyb id o ac i e
solu ions. Despi e he inhe en limi a ions o simula ion p og ams and he unce ain y
associa ed wi h clima e p ojec ions, his s udy aims o lay he ounda ions o mo e
comp ehensi e u u e ene gy analyses, also conside ing he socioeconomic dimension,
whe e po e y indica o s will be o g ea help.

Pàg. 6 Memò ia
CONTENTS
RESUM ____________________________________________________ 3
RESUMEN _________________________________________________ 4
ABSTRACT _________________________________________________ 5
CONTENTS _________________________________________________ 6
ABBREVIATIONS AND SYMBOLS ______________________________ 8
LIST OF FIGURES __________________________________________ 10
LIST OF TABLES ___________________________________________ 14
1. PREFACE _____________________________________________ 15
2. INTRODUCTION ________________________________________ 16
2.1. Mo i a ion ................................................................................................. 17
2.2. Scope ....................................................................................................... 17
2.3. P e equisi es ............................................................................................ 18
2.4. Objec i es ................................................................................................ 19
3. THEORETICAL BACKGROUND ___________________________ 20
3.1. Concep s .................................................................................................. 20
3.1.1. Building esilience ....................................................................................... 20
3.1.2. The mal com o .......................................................................................... 20
3.1.3. Ene gy po e y ............................................................................................ 21
3.2. Indica o s.................................................................................................. 22
3.2.1. Resilience indica o s ................................................................................... 22
3.2.2. Com o indica o s ....................................................................................... 24
3.3. Cooling s a egies .................................................................................... 28
3.4. S a e o he a .......................................................................................... 31
4. METHODOLOGY _______________________________________ 42
4.1. Wea he da a ........................................................................................... 43
4.1.1. Da a collec ion ............................................................................................. 43
4.1.2. S udied scena ios ........................................................................................ 44
4.1.2.1. TMY ............................................................................................ 44
4.1.2.2. HW ............................................................................................. 44
4.2. Modelled building ..................................................................................... 45
4.2.1. Building’s loca ion ....................................................................................... 45
4.2.2. Geome y and en elope .............................................................................. 47
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 7
4.2.3. Loads and schedules .................................................................................. 54
4.3. Simula ions .............................................................................................. 58
4.3.1. Simula ion ools ........................................................................................... 59
4.3.2. Cooling echnologies ................................................................................... 60
4.3.3. S udied scena ios ........................................................................................ 63
5. RESULTS _____________________________________________ 65
5.1. Resilience analysis base case ................................................................. 65
5.1.1. Resilience analysis ...................................................................................... 65
5.1.2. Com o analysis ......................................................................................... 70
5.2. Resilience analysis wi h cooling echnologies ......................................... 80
5.2.1. TMY Analysis .............................................................................................. 80
5.2.1.1. Resilience s udy ......................................................................... 80
5.2.1.2. Com o s udy ............................................................................. 81
5.2.2. HW Analysis ................................................................................................ 85
5.2.2.1. Resilience s udy ......................................................................... 86
5.2.2.2. Com o s udy ............................................................................. 87
6. DISCUSSION __________________________________________ 94
6.1. Resilience analysis, buildings compa ison o he base cases ................. 97
6.2. Resilience analysis, buildings compa ison wi h cooling echnologies
implemen ed .......................................................................................... 103
7. PLANNING ___________________________________________ 113
8. ECONOMIC ASSESSMENT ______________________________ 115
8.1. Cos s o hou s dedica ed ....................................................................... 115
8.2. Cos s o ma e ials .................................................................................. 116
9. ENVIRONMENTAL ASSESSMENT ________________________ 117
10. SOCIAL AND GENDER EQUALITY ASSESSMENT ___________ 120
11. CONCLUSIONS _______________________________________ 122
12. LIMITATIONS AND FUTURE WORK _______________________ 124
13. BIBLIOGRAPHY _______________________________________ 126
Pàg. 8 Memò ia
Abb e ia ions and Symbols
α: Alpha
AC: Ai condi ioning
AdWind: Ad anced Windows
AWD: Ambien Wa mness Deg ee
BC: Base Case
BC_CM: Base Case building in Ciu a Me idiana
BC_TY: Base Case Typical building in Ca alunya
BL: Blinds
CHE: Cold Hou s o Exceedance
CM: Ciu a Me idiana’s building
CORDEX: Coo dina ed Regional Clima e Downscaling Expe imen
CTE: Código Técnico de Edi icación
DI: Discom o Index
G R : G een Roo
HHE: Annual Ho Hou s o Exceedance
HI: Hea Index
HVAC: Hea ing, Ven ila ion, and Ai Condi ioning
HW: Hea Wa es
HW_LF_MI: Hea Wa e, Long Fu u e, Mos In ense.
HW_LF_LMS: Hea Wa e, Long Fu u e, Longes and Mos Se e e
HW_MF_L: Hea Wa e, Mid Fu u e, Longes
HW_MF_MIS: Hea Wa e, Mid Fu u e, Mos In ense and Se e e
HW_P_L: Hea Wa e, P esen , Longes
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 9
HW_P_MI: Hea Wa e, P esen , Mos In ense
HW_P_MS: Hea Wa e, P esen , Mos Se e e
IOD: Indoo O e hea ing Deg ee
IPCC: In e go e nmen al Panel on Clima e Change
L: Longes
LF: Long Fu u e
LMS: Longes and Mos Se e e
MF: Mid Fu u e
MI: Mos In ense
MIS: Mos In ense and Se e e
MS: Mos Se e e
NV: Na u al Ven ila ion
OG: Base Case
OS: OpenS udio
P: P esen
SCOP: Seasonal Coe icien o Pe o mance
SEER: Seasonal ene gy e iciency a io
TMY: Typical Me eo ological Yea
TMY_LF: Typical Me eo ological Yea , Long Fu u e
TMY_MF: Typical Me eo ological Yea , Mid Fu u e
TMY_P: Typical Me eo ological Yea , P esen
TY: The mos ep esen a i e/ ypical building in Ba celona
Pàg. 16 Memò ia
2. In oduc ion
Day by day, he impac s o clima e change a e inc easingly e iden in ou li es, b inging
se e e wea he e en s ha de as a e landscapes, buildings, and communi ies. This eali y
has been demons a ed epea edly, ye some indi iduals con inue o igno e o downplay i s
signi icance. Un o una ely, he mos oubling ac emains: he wo s impac s a e s ill
ahead. Majo clima e shi s will soon begin o dis up owns, cul u es, and he wo ld as we
know i .
These changes will a ec he mos ulne able popula ions i s , hose who a e no well
p epa ed and can’ a o d o eno a e hei homes [69]. Mo eo e , people esiding in al eady
wa m egions o opical clima es will expe ience he ea lies and mos p o ound e ec s [15]
[19] [30]. This p essing issue unde sco es he u gen need o de elop solu ions ha can
ei he s op global wa ming o a leas signi ican ly mi iga e i s p og ession be o e i is oo
la e. Meanwhile, solu ions on how o mi iga e he e ec s o clima e change a e also equi ed
o species o li e com o ably du ing ex eme wea he e en s.
Gi en he in ensi ying equency o hese abno mal e en s [45], dwellings and shel e s mus
be p epa ed o wi hs and hese changes and p o ide essen ial com o o hei inhabi an s.
E en he ones wi h no much inancial income. This is exac ly he ocus o his pape , which
aims o s udy and p opose di e en echnologies o a low-income household o lessen he
e ec s o clima e change in i s esilience and com o .
The u u e o building design emphasizes ene gy e iciency and clima e esilience, aiming
o educe CO₂ emissions and p omo e a low-emission u u e ha includes “passi e houses”
[17]. A "passi e house" does no ely on ac i e echnologies, which use elec ici y o ene gy
o wo k; ins ead, i main ains com o able empe a u es h ough low-ene gy, enewable o
passi e echnologies, he ones ha don’ use ene gy o wo k [38]. Al hough his s udy does
no ocus speci ically on passi e houses, i p esen s a comp ehensi e analysis o he
he mal pe o mance o low-income household and he a ious cooling s a egies a ailable
o enhance com o . These s a egies mus be cos -e ec i e o low-income esiden s,
allowing hem o achie e com o wi h minimal o no addi ional ene gy consump ion, such
as he solu ions used in passi e houses [27].
By simula ing cu en and u u e clima e scena ios, his esea ch seeks o iden i y and
compa e e ec i e me hods o imp o ing indoo he mal com o while educing ene gy use
and en i onmen al impac . This s udy builds on p e ious wo ks, pa icula ly hose by En ico
Ton odona i, Albe Massana, Ma ina A iza, and Oswin C espo [70] [46] [51] [48], who
examined how he mos common building ype in Ca alonia esponds o he egion’s ou
dis inc clima ic zones: Ba celona, San Sal ado de Gua diola, Bages and Seu d’U gell. By
adap ing hese me hodologies and ocusing on a di e en building, his esea ch p o ides
new insigh s in o he e icacy o passi e and ac i e cooling op ions o low-income

Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 17
households.
The co e message o his pape is o highligh he g a i y o he clima e c isis i we ail o
ac , emphasizing ha he leas ad an aged popula ions will be among he i s o bea i s
consequences.
2.1. Mo i a ion
Clima e change is inc easingly e iden , wi h ex eme wea he e en s such as hea wa es,
loods, and d ough s becoming mo e equen . Rising sea le els, he accumula ion o
ca bon dioxide in he soil, and highe empe a u es a e some o he no able consequences
[21] . As he e ec s o clima e change in ensi y, he e is an u gen global need o ene gy-
e icien solu ions o p e en hese impac s om becoming i e e sible.
These solu ions can be classi ied in o ac i e and passi e ca ego ies. Ac i e solu ions, such
as ansi ioning om ossil uel-based ene gy sou ces o enewable al e na i es, di ec ly
add essing he oo causes o clima e change. In con as , passi e solu ions aim o mi iga e
i s e ec s on exis ing s uc u es and sys ems.
The p ima y objec i e o his p ojec is o examine how global wa ming may a ec he
com o and well-being o indi iduals, pa icula ly in ela ion o he buildings hey inhabi .
This s udy will explo e po en ial solu ions o e o i ing buildings o enhance hei esilience
and ene gy e iciency, ollowing a simula ion analysis.
Fu he mo e, his esea ch aims o highligh a ulne able segmen o he popula ion ha
has o en been o e looked: indi iduals wi h low-income housing. I is impo an o
acknowledge he challenges aced by his g oup, especially in accessing addi ional ene gy
esou ces du ing ex eme wea he e en s. These indi iduals a e less likely o be able o
mi iga e discom o in hei homes, which can lead o signi ican heal h p oblems and a
decline in o e all quali y o li e.
This s udy unde sco es he impo ance o add essing he needs o disad an aged
communi ies in he b oade con ex o clima e change adap a ion and ene gy e iciency.
2.2. Scope
The i s phase o his pape in ol es de ining a s uc u ed S a e o he A , compiling
p e ious esea ch on ene gy po e y de ec ion and assessmen . A e iew o a ious
indica o s used o e alua e ene gy po e y bo h locally and globally is conduc ed.
Addi ionally, o he s udies p oposing solu ions o mi iga e he e ec s o clima e change on
Pàg. 18 Memò ia
ulne able buildings a e also discussed. Howe e , his hesis will co e only he ene gy
analysis h ough simula ions; no su eys o de ailed economic esea ch will be ca ied ou .
The second phase o he esea ch ocuses on simula ing and analysing di e en clima ic
scena ios o assess hei impac on he mos common ype o building ound in he mos
disad an aged neighbou hoods o Ba celona.
Fi s , a ho ough in es iga ion is ca ied ou o iden i y he poo es neighbou hood in
Ba celona and de e mine he mos ypical building ype loca ed he e. Once his in o ma ion
is ob ained, he building is modelled om sc a ch, and he inpu a iables o he simula ions
a e de ined.
Clima ic da a o Ba celona is p o ided by p e ious s udies [70] and will be used o simula e
h ee dis inc scena ios: he p esen (2009-2028), he mid- e m u u e (2040-2060), and he
long- e m u u e (2080-2100). A p ima y cons ain iden i ied ea ly in he s udy was he
signi ican amoun o ime equi ed o ob ain and p ocess he wea he da a in p epa a ion
o inpu in o he Open S udio p og am. Howe e , due o he se e al Py hon sc ip s o
op imize he pos -p ocessing o he da a, his p oblem was sol ed [61].
Addi ionally, he s udy will examine he p edic ed e ec s o inc easingly in ense and
p olonged hea wa es in u u e yea s, as he main ex eme wea he e en s udied. A u he
limi a ion a ises om he ac ha he u u e wea he da a is based on s a is ical analysis
and ma hema ical algo i hms, meaning he esul s a e subjec o po en ial changes, as hey
ep esen p ojec ions o u u e condi ions a he han ce ain ies.
The main objec i e o his s udy is o calcula e a se o esilience indica o s designed o
add ess he mal com o inside dwellings. These indica o s will be applied o di e en
building scena ios, s a ing wi h a base case building model wi hou any cooling s a egies.
This base case will hen be compa ed o he same building wi h a ious cooling s a egies
implemen ed o assess hei e ec i eness in imp o ing ene gy esilience.
2.3. P e equisi es
To ini ia e he p ojec , i is essen ial o ha e a solid unde s anding o key concep s such as
esilience, he mal com o , and ene gy po e y, as hese a e undamen al o
comp ehending he impac s o clima e change on people's li es.
Addi ionally, a ho ough e iew o he concep o ene gy po e y mus be conduc ed,
pa icula ly because i is o en con used wi h he concep o uel po e y [40]. An ex ensi e
in es iga ion is ca ied ou o examine how di e en coun ies, wi hin hei espec i e
con ex s, iden i y ene gy po e y, he indica o s hey use, and he s a egies hey implemen
o mi iga e i . This deepe unde s anding o ene gy po e y is needed o selec he
app op ia e neighbou hood whe e he s udy will ake place.
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 19
Fu he mo e, acqui ing a solid unde s anding o cooling echnologies is necessa y o
add ess he discom o expe ienced in esiden ial se ings.
Au onomous lea ning o OpenS udio and Ene gyPlus is also necessa y, as hese ools ha e
no been p e iously used. In addi ion, a ounda ional knowledge o Py hon is essen ial o
e ec i ely execu ing he sc ip s equi ed o op imize he esul s o he simula ion p ocess.
2.4. Objec i es
As p e iously ou lined, he main objec i e o his p ojec is o s udy how clima e change will
a ec he esilience and ene gy e iciency o he mos common building ype o he
neighbou hood wi h he lowes income in Ba celona.
To achie e his, se e al speci ic goals mus be pu sued:
• In es iga e he concep o ene gy po e y and de elop an ex ensi e S a e o he A
wi h s udies on use ul indica o s o quan i ying ene gy po e y and how his
p oblem a ec s low-income households.
• Analyse he poo es neighbou hood in Ba celona o iden i y he mos common
building ype, s uc u e, o ien a ion, and he ypes o equipmen implemen ed.
• Model he building selec ed o his s udy using Ske chUp and OpenS udio so wa e.
• Re iew which cooling echnologies and s a egies can be applied in a low-income
household, such as he one ha will be modelled in he s udy.
• Simula e he building model unde di e en clima e scena ios, applying each o he
iden i ied cooling s a egies o assess hei e ec i eness.
• Calcula e he com o and esilience indica o s, used in p e ious wo ks [70] [46], o
e alua e which cooling s a egies p o ide he bes esilience ou comes.
• Combine he mos e icien s a egies and simula e he combina ion cases o
op imize building esilience and ene gy e iciency.
• Ob ain esilience and com o indica o s esul s o he combina ions chosen and
analyse hem.
Pàg. 20 Memò ia
3. Theo e ical backg ound
In his sec ion, he main concep s and de ini ions essen ial o unde s anding he p esen
s udy, i s me hodology, and subsequen esul s a e in oduced. All in o ma ion has been
ga he ed om a e iew o academic a icles, heses, and o he esea ch wo ks wi hin he
ields o building esilience, ene gy e iciency, and he mal com o .
3.1. Concep s
3.1.1. Building esilience
Building esilience can be de ined as he abili y o a building o adap o, espond o, and
eco e om ad e se clima ic condi ions while ensu ing he sa e y, com o , and well-being
o i s occupan s wi h minimal ene gy and en i onmen al impac [66]. In a con ex
inc easingly ma ked by ex eme wea he e en s due o clima e change, such as hea wa es,
p olonged d ough s, and in ense ain all, esilience plays a cen al ole in bo h he design
and e o i ing o he buil en i onmen [33].
This concep goes beyond me e s uc u al esis ance and encompasses he building's
capaci y o main ain habi able and com o able indoo condi ions, pa icula ly du ing
clima e- ela ed c ises, wi hou elying exclusi ely on ene gy-in ensi e mechanical sys ems
[33]. Thus, esilience becomes an in eg a ed measu e o he building's passi e he mal
esponse, he ene gy e iciency o i s sys ems, and i s adap abili y o u u e scena ios o
g ea e clima ic se e i y.
The in eg a ion o passi e cooling s a egies such as na u al en ila ion, g een oo s, sola
shading, and high-pe o mance windows con ibu es o enhancing a building’s clima e
esilience by educing dependence on ac i e cooling sys ems and, consequen ly, lowe ing
ene gy consump ion and associa ed emissions [25]. The e o e, esilience analysis in
buildings is a key ool o sus ainable design and o p epa ing he buil en i onmen o ace
bo h cu en and u u e clima e challenges.
3.1.2. The mal com o
The mal com o was de ined by Hensen e al. [25] e e ed o he condi ion in which
occupan s pe cei e hei he mal en i onmen as sa is ac o y. I is in luenced by a
combina ion o en i onmen al a iables, indoo ai empe a u e, ela i e humidi y, ai
eloci y as well as indi idual ac o s such as me abolic a e and clo hing insula ion [81]. As
a c i ical me ic in he assessmen o indoo en i onmen al quali y, he mal com o is
di ec ly ied o ene gy pe o mance and occupan p oduc i i y.
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 21
In ecen decades, an h opogenic clima e change has signi ican ly al e ed ecosys ems and
he buil en i onmen , pa icula ly in Medi e anean egions, whe e he equency and
in ensi y o hea wa es ha e inc eased ma kedly [53]. These e en s pose se ious isks no
only o human heal h and p oduc i i y bu also o ene gy in as uc u es, o en leading o
su ges in cooling demand and an inc eased p obabili y o powe ou ages. Such condi ions
can se e ely comp omise he mal com o and, in ex eme cases, he su i abili y o
ulne able occupan s wi hin esiden ial buildings.
The mal com o is especially ele an when e alua ing he pe o mance and esilience o
buildings unde bo h cu en and u u e clima ic scena ios. As demons a ed p e ious
s udies [70] [43], he mal com o is closely linked o he building’s design, he e ec i eness
o passi e and ac i e cooling s a egies, and he building en elope’s capaci y o mi iga e
indoo o e hea ing. Du ing hea wa es o powe ou ages, main aining he mal com o
becomes pa icula ly challenging, unde sco ing he impo ance o esilien a chi ec u al and
echnological solu ions.
In his con ex , Ensecu e Al. [28] said ha he mal com o is assessed no only by
quan i a i e indica o s such as ope a i e empe a u e and hou s o exceedance o e
es ablished h esholds, bu also by quali a i e pe cep ions o he occupan s. I is hus a
mul idimensional concep ha in e sec s heal h, ene gy pe o mance, and building
esilience. Ensu ing accep able le els o he mal com o unde u u e clima e condi ions
equi es he in eg a ion o passi e cooling echniques—such as na u al en ila ion, g een
oo s, blinds, and high-pe o mance windows—as well as a s a egic use o ai condi ioning
sys ems, all o which con ibu e o educing en i onmen al impac and ene gy- ela ed cos s
[33].
3.1.3. Ene gy po e y
Ene gy po e y is a mul idimensional social and economic phenomenon ha e lec s a
household’s inabili y o access essen ial ene gy se ices necessa y o main ain a basic and
decen s anda d o li ing [64]. Acco ding o he de ini ion p o ided by he Ene gy E iciency
Di ec i e, ene gy po e y e e s o he lack o access o undamen al ene gy se ices such
as adequa e hea ing, ho wa e , cooling, ligh ing, and elec ici y o appliances wi hin he
con ex o na ional s anda ds, social policies, and li ing condi ions [4].
This condi ion a ises om a con luence o s uc u al and socioeconomic ac o s. Chie
among hose a e he una o dabili y o ene gy, insu icien disposable household income,
excessi e ene gy expendi u es ela i e o income, and he poo ene gy e iciency o
esiden ial buildings. When ene gy cos s consume a disp opo iona ely high sha e o a
household’s income, i can signi ican ly impai he abili y o mee o he basic needs such as
ood, heal hca e, and educa ion. Mo eo e , in an e o o minimize cos s, a ec ed

Pàg. 22 Memò ia
households may educe hei ene gy consump ion o le els ha a e de imen al o hei
physical and men al heal h, leading o ad e se ou comes such as he mal discom o ,
espi a o y illnesses, and social exclusion [55].
This si ua ion is agg a a ed by he impac s o clima e change. Global wa ming leads o a
disp opo iona e inc ease in ene gy consump ion, he eby wo sening he economic
condi ions o households al eady in ulne able si ua ions. As a esul , esiden s expe ience
g ea e discom o due o he inabili y o main ain com o able indoo empe a u es.
Ene gy po e y, he e o e, is no only an issue o ene gy access, bu also o a o dabili y,
equi y, and housing quali y [64]. Add essing i equi es an in eg a ed policy app oach ha
encompasses ene gy e iciency imp o emen s, income suppo mechanisms, and a ge ed
social in e en ions o ensu e ha all indi iduals can enjoy a minimum s anda d o ene gy
se ices necessa y o heal h, well-being, and social pa icipa ion.
3.2. Indica o s
In o de o assess he esilience o buildings o he impac s o clima e change, a ious
indica o s cu en ly employed in o he s udies [70] [45]. These indica o s p o ide aluable
insigh s in o a building’s abili y o main ain indoo he mal com o unde inc easingly
ex eme clima ic condi ions.
3.2.1. Resilience indica o s
One o he p ima y objec i es o he The mal Condi ion Task Fo ce, es ablished in Ap il
2020 as pa o EBC Annex 80, Resilien Cooling o Buildings [60], was o de ine a
s anda dized benchma k ha acili a es he global compa ison o di e en cooling
echnologies. This amewo k no only accoun s o ene gy e iciency bu also inco po a es
occupan com o in he e alua ion o building esilience. I pu sues wo main goals [12]:
1. To de ine a s anda dized benchma k o compa ing a ious cooling echnologies
wo ldwide.
2. To es ablish he mal condi ions o assessing di e en cooling echnologies.
The amewo k p oposes h ee dis inc indica o s o e alua e esilience:
Indoo o e hea ing deg ee (IOD)
This indica o e lec s he isk o o e hea ing wi hin he dwelling, conside ing all he dis inc
he mal zones and hei speci ic com o h esholds, which a y acco ding o occupan
beha iou in each space. As a esul , i enables he e alua ion o bo h he o e all in ensi y
and equency o indoo o e hea ing.
The in ensi y o he o e hea ing is calcula ed as he posi i e empe a u e di e ence
be ween he indoo ope a i e empe a u e and he de ined com o empe a u e limi ,
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 23
es ablished a 26ºC acco ding o he UNE-EN-ISO 16798-1 s anda d [51].
The equency is de e mined by in eg a ing his empe a u e di e ence o e he pe iods
du ing which he zone is occupied.
𝐼𝑂𝐷 = ∑ ∑ [(𝑇𝑜𝑝,𝑖,𝑧−𝑇𝑐𝑜𝑚𝑓,𝑖,𝑧)+·𝑡𝑖,𝑧]
𝑁𝑜𝑐𝑐(𝑧)
𝑖=1
𝑧
𝑧=1
∑ ∑ 𝑡𝑖,𝑧
𝑁𝑜𝑐𝑐(𝑧)
𝑖=1
𝑧
𝑧=1 (1)
Whe e he a iables ep esen :
- 𝑖 = Index ep esen ing he occupied hou s.
- 𝑡 = The ime s ep conside ed in he analysis.
- 𝑁𝑜𝑐𝑐 = Index ep esen ing he occupied hou s.
- 𝑧 = The di e en he mal zones wi hin he building.
- 𝑇𝑜𝑝,𝑖,𝑧 = The ope a i e empe a u e in zone z du ing he occupied hou i.
- 𝑇𝑐𝑜𝑚𝑓,𝑖,𝑧 = The com o empe a u e in zone z du ing he occupied hou i. As
p e iously men ioned, his empe a u e is se o 26 °C du ing summe ope a ional
hou s.
Ambien wa mness deg ee (AWD)
This indica o quan i ies he se e i y o ou doo ai empe a u es exceeding a de ined
e e ence empe a u e, Tb. The e e ence empe a u e should be selec ed based on he
building ype and local clima ic condi ions. In his s udy, i is se o 18 °C, which is conside ed
he lowe h eshold o summe he mal com o . Consequen ly, in any scena io whe e he
ou doo ai empe a u e exceeds 18 °C, he AWD indica o assumes alues g ea e han
ze o [12].
𝐴𝑊𝐷18º𝐶 = ∑[(𝑇𝑎,𝑖−𝑇𝑏)+·𝑡𝑖]
𝑁
𝑖=1 ∑𝑡𝑖
𝑁
𝑖=1 (2)
Whe e he a iables ep esen :
- 𝑖 = Index ep esen ing he occupied hou s.
- 𝑁 = The numbe o occupied hou s whe e 𝑇𝑎,𝑖 > 𝑇𝑏
- 𝑡 = The ime s ep conside ed in he analysis.
- 𝑇𝑎,𝑖 = The ou doo empe a u e du ing he occupied hou i.
- 𝑇𝑏 = The lowes limi empe a u e o summe com o .
O e hea ing escala ion ac o (α)
This indica o e lec s he building’s sensi i i y o o e hea ing. The pa ame e α ep esen s
Pàg. 24 Memò ia
he slope o he eg ession line be ween he Indoo O e hea ing Deg ee (IOD) and he Ai
Wa m Deg ee (AWD). I akes only posi i e alues. A lowe α alue indica es g ea e
esilience o he building o he impac s o clima e change.
𝛼 = 𝐼𝑂𝐷
𝐴𝑊𝐷18º𝐶 (3)
3.2.2. Com o indica o s
As his s udy aims o analyse he he mal esilience o buildings unde clima e change
condi ions, speci ically hei abili y o main ain sa e and com o able indoo empe a u es,
addi ional com o - ela ed indica o s will also be examined.
Com o indica o s, whe he based on di ec o indi ec empe a u e measu emen s, p o ide
aluable insigh in o he e ec s o clima e change on he mal condi ions wi hin a dwelling.
These indica o s assess he building’s capaci y o wi hs and ex eme wea he e en s, such
as hea wa es, by e alua ing he he mal sensa ion expe ienced by occupan s in a ious
zones o he building.
The mal com o is gene ally conside ed o be achie ed when indoo empe a u es ange
be ween 23°C and 27°C du ing summe , and be ween 20°C and 25°C in win e [80].
Following he me hodology p oposed by Ton odona i [70], he ollowing indica o s ha e
been chosen o his s udy:
Hea Index (HI)
This index ep esen s he empe a u e ha he human body eels when ai empe a u e is
combined wi h ela i e humidi y, his is he appa en empe a u e [78]. This HI alues a e
calcula ed by a collec ion o equa ions ha comp ise a model ye , he e is a educed
ela ionship be ween d y bulb empe a u es a di e en humidi y and he skin's esis ance
o hea and mois u e ans e . The compu a ion o HI is a e inemen o a mul iple eg ession
analysis done by Lans P. Ro hdusz [59]. The eg ession equa ion is as ollows:
𝐻𝐼 = −42.379+ 2.04901523 · 𝑇 + 10.14333127·𝑅𝐻 − 0.22475541· 𝑇· 𝑅𝐻
−0.00683783·𝑇2−0.05481717·𝑅𝐻2· + 0.00122874· 𝑇2·𝑅𝐻
+0.00085282·𝑇·𝑅𝐻2−0.00000199·𝑇2·𝑅𝐻2
(4)
Whe e he a iables ep esen :
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 25
- 𝑇 = Ai empe a u e in deg ees Fah enhei [°F]
- 𝑅𝐻 = Rela i e humidi y in pe cen age [%]
Howe e , his index has a limi a ion: when he calcula ed alue is below 80°F, he Ro h usz
eg ession is no conside ed app op ia e. In such cases, a simpli ied o mula is applied o
ensu e consis en and eliable alues [46]:
𝐻𝐼 = 0.5·( 𝑇+ 61.0+[ {𝑇−68.0}· 1.2 ]+[𝑅𝐻·0.094] ) (5)
I he alue is e en lowe , below 26.66°F, he Ro h usz eg ession becomes unsui able. In
such cases, a simpli ied o mula is employed o ensu e consis en and accu a e esul s [46]:
𝐻𝐼 = 1.1∙𝑇+0.0261∙𝑅𝐻−3.94 (6)
This index classi ies hea s ess in o ou p ima y dange le els, based on he cha p o ided
by he U.S. Na ional Wea he Se ice, as illus a ed in Figu e 1.
Fig 1. Hea Index lookup able [50]
Classi ica ion
Hea index
E ec on he body
Sa e condi ions
26.7ºC o lowe
No e ec s
Cau ion
26.7ºC – 32.2ºC
Possible a igue due o p olonged exposu e o
physical ac i i y
Ex eme Cau ion
32.3ºC – 39.4ºC
P olonged exposu e o physical ac i i y may
esul in condi ions such as hea s oke, hea
c amps o hea exhaus ion
Pàg. 32 Memò ia
ulne able households. Wi hin he cu en socioeconomic con ex , no all households can
bea he inc eased ene gy cos s equi ed o adequa ely clima e hei homes. Consequen ly,
cu en esea ch is ocusing on passi e s a egies, hose ha do no consume ene gy o
p o ide indoo he mal com o [39].
Recen s udies, such as ha by S asi e al. [67], explo ed he po en ial o na u al en ila ion
as a s a egy o add ess ene gy po e y, pa icula ly in low-income se ings.
None heless, o e ec i ely ackle his challenge, i is essen ial o iden i y and loca e
households expe iencing ene gy po e y, as his condi ion g ea ly limi s access o adequa e
clima iza ion echnologies.
Se e al s udies ha e ocused on he de ailed analysis o many o he ene gy po e y
indica o s cu en ly used by bo h he Eu opean Union and indi idual coun ies [65] [18].
These wo ks compa e a ious indica o s o p o ide a comp ehensi e o e iew o exis ing
me hods o de ec ing ene gy po e y, anging om objec i e and subjec i e indica o s o
Hidden Ene gy Po e y (HEP) indica o s, as well as combina ions wi h o he esilience and
com o me ics. An example o his app oach is he s udy conduc ed by Kez, Foley,
Lowans, and Del Rio [6], in which he Thom’s Discom o Index (de ined in sec ion 3.2.2)
was also analysed and linked o ene gy po e y.
A he na ional le el, in Ap il 2019, he Spanish Go e nmen app o ed he Na ional
S a egy agains Ene gy Po e y 2019-2024, ENPE [1], which is a p oposed a s a egy
ha can be summa ized in six poin s:
1. O icial de ini ion o ene gy po e y.
2. P opo ion o he Spanish popula ion expe iencing ene gy po e y, acco ding o he
indica o s es ablished by he EU Ene gy Po e y Obse a o y.
3. Recommenda ion o an in-dep h e alua ion o household ene gy spending pa e ns
in Spain.
4. Iden i ica ion o he limi a ions o cu en social a i s and sugges ions o implemen
uni ied inancial assis ance co e ing all ene gy se ices.
5. P oposal o s uc u al in e en ions in he sho , medium, and long e m, including
ene gy e iciency upg ades in homes o ulne able popula ions.
6. Ini ia i es aimed a inc easing public awa eness o ene gy po e y and enhancing
households' access o ele an in o ma ion.
Apa om he p oposal o he ENPE, se e al p ojec s and s udies ha e al eady been
conduc ed in Spain aiming o de elop local ene gy po e y indica o s in o de o iden i y
and, whe e possible, p e en such si ua ions.
The COOLTORISE p ojec , coo dina ed by esea che s a he Uni e sidad Poli écnica de
Mad id and unded by he Eu opean Commission h ough he Ho izon 2020 p og am, aims
o educe cooling needs ac oss Eu ope by aising awa eness abou summe ene gy po e y
[55]. I s main objec i e is o lessen he incidence o summe ene gy po e y in Eu opean

Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 33
households by imp o ing indoo he mal condi ions and lowe ing ene gy consump ion
du ing he ho season. To ul il i s mission, he p ojec es ablished six speci ic objec i es o
be add essed [55]:
• Es ablish a common amewo k o unde s anding summe ene gy po e y.
• De ine e ec i e solu ions o mi iga e summe ene gy po e y.
• T ain ene gy po e y agen s o wo k di ec ly wi h a ec ed households.
• Alle ia e he si ua ion o summe ene gy po e y o mo e han 7240 indi iduals.
• P omo e women's empowe men o help coun e ac he eminiza ion o ene gy
po e y.
• Achie e widesp ead dissemina ion o aise awa eness abou he p oblem o
summe ene gy po e y.
The p ojec s a ed in Mad id in 2021 [73] and he in e en ion a eas we e selec ed based
on an assessmen o he u ban hea island e ec , ocusing on zones whe e en i onmen al
ulne abili y o e laps wi h signi ican social ulne abili y. Wi h he aim o add essing hese
challenges h ough gende empowe men , Cool o ise designed inclusi e ac i i ies ha
acili a e wo k-li e balance, such as lexible wo kshops and pa allel childca e spaces.
Addi ionally, he p ojec implemen ed ini ia i es a ge ing amilies o educe hei ene gy
needs and enhance he mal com o du ing he summe . These included ene gy and hea
li e acy wo kshops p omo ing passi e cooling s a egies, such as he e icien use o na u al
en ila ion and shading echniques, and sessions ocused on unde s anding ene gy bills
and imp o ing ene gy consump ion e iciency.
In Se ille, Alba-Rod íguez e al. [6] analysed 40 social housing uni s p ojec ed o he yea s
2050 and 2080, adop ing a holis ic app oach ha conside s ene gy consump ion, heal h,
com o , and mone a y po e y. This s udy in oduces an in e es ing indica o o de e mine
ene gy po e y, he Vulne able Household Index (IVH). Cu en indica o s ail o accoun
o u u e clima e change scena ios, highligh ing he need o a mo e holis ic app oach. A
comp ehensi e analysis o ene gy managemen is essen ial o ensu e minimum habi abili y
s anda ds in homes and he IVH indica o p e ends o add ess his by combining social
aspec s, such as esiden s' heal h and household economic condi ions, wi h ene gy
e iciency ac o s and u u e p ojec ions.
The exis ing indica o includes a ious social indices and pa ame e s, sca e ed in ou
di e en pa s.
• Mone a y Po e y Indica o (MPI): This componen assesses he household's
economic ulne abili y by in eg a ing egion-speci ic indica o s, speci ically he
Mone a y Po e y Th eshold (MPT) and he Se e e Mone a y Po e y Th eshold
(SMPT).
Pàg. 34 Memò ia
• Ene gy Indica o (EnI): This indica o e alua es he equi ed household ene gy
consump ion (EC) agains a designa ed ene gy h eshold es ablished o he
neighbou hood. The h eshold is de e mined ollowing he EN 16798-1:2019
s anda d [71].
• Com o Indica o (CI): The he mal com o model employed wi hin he IVH
amewo k examines he ela ionship be ween ou doo and indoo empe a u es. I
his ela ionship emains wi hin he p ede ined com o ange, he occupan s a e
assumed o be in a he mally com o able s a e. The model calcula es he
pe cen age o hou s du ing which he di e ence be ween indoo and ou doo
empe a u es exceeds he accep able com o ange. A com o h eshold o 80% is
applied, accoun ing o he assump ion ha he emaining 20% o he ime
co esponds o sleeping hou s. The EN 16798-1:2019 s anda d [71] ou lines ou
ca ego ies o accep able indoo he mal condi ions, depending on occupan
expec a ions and he building's age.
• Heal h-Rela ed Quali y o Li e Cos (HRQLC): This componen quan i ies he
heal h- ela ed cos using he Quali y-Adjus ed Li e Yea (QALY) me ic, which is
linked o each le el o ulne abili y de ined wi hin he IVH, as illus a ed in Figu e 2.
Figu e 3 is a summa y scheme o he me hodology o calcula ing he implemen ed Index
IVH ob ained om Alba-Rod íguez e al. [6].
Fig 4. Me hodology implied o calcula ing he IVH [6]
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 35
Sánchez-Gue a a e al. [64] p esen ed an index o iden i ying u ban ene gy po e y a he
municipal and dis ic le el, he High Ene gy Requi emen Index (HER). This index is used
o map he ene gy po e y issue h ough nine de e mining ac o s o ene gy po e y: Ne
income, g oss disposable income pe capi a, a e age annual pension pe capi a, building
yea o cons uc ion, building main enance, hea ing sys em a ailabili y, cooling sys em
a ailabili y, elec ic hea ing sys em, dwelling su ace by household membe and U ban Hea
Island (UHI).
The le el o he dis ic s’ ulne abili y owa ds ene gy po e y is assessed based on h ee
di e en ci cums ances when analysing hese de e mining ac o s [64]:
- The numbe o a iables analysed as de e mining ac o s o ene gy po e y:
dis ic s ha ing he la ges numbe o ac o s a e wo se han he ci y
a e age.
- The wo s alues: dis ic s p esen ing he wo s alue o each ac o .
- Accumula ion o se e al indica o s: dis ic s ga he ing c i ical alues in
se e al indica o s, al hough hey do no p esen he la ges numbe o
ac o s, no a e hei indica o alues he wo s .
A mo e speci ic explana ion o his nine de e mining ac o s is conduc ed. Fi e o hem a e
p oxy indica o s ela ed o esiden ial ene gy use:
1. Yea o cons uc ion: % o buildings buil be o e 1980, as hose buil be o e his yea
do no mee he i s Spanish legisla ion ela ed o insula ion (NBE-CT- 79), and
he e o e exhibi a p esumably de icien he mal beha iou .
2. Main enance condi ions: % o buildings wi h dilapida ed, bad, o de icien
main enance condi ions
3. Hea ing a ailabili y (di e en ia ing hose using elec ic hea ing sys ems as hey use
he mos expensi e ene gy): % o households in dwellings wi hou any hea ing
sys ems. Those who may use po able o elec ic hea e s, which a e less e icien
and mo e expensi e
4. Cooling a ailabili y (di e en ia ing hose using elec ic hea ing sys ems, as hey use
he mos expensi e ene gy): % o buildings ha lack cooling sys ems. Tha may
in ol e a highe expendi u e and isk o he mal discom o .
5. Welling su ace by household membe : he 𝑚2 su ace a ea o be condi ioned
di ec ly in luences he house’s ene gy needs. A highe Su ace means a highe
impac on he ene gy expendi u e.
Th ee addi ional indica o s e lec ing he household’s income we e added:
6. The ne income: A e age household disposable income calcula ed om he o al
membe s’ income a e axes and social secu i y con ibu ions.
7. The g oss disposable income pe capi a: A e age income pe capi a, excluding he
ans e o capi al, p o i s, and loss o ac ual possessions, and he consequence o
na u al disas e e en s.
8. The a e age annual income: A e age annual income disagg ega ed by sex and
membe .
Pàg. 36 Memò ia
This las ac o is included o e lec he in luence o he ising empe a u es issue due o
clima e change on ene gy po e y de ec ion:
9. The UHI in ensi y was also included because empe a u e di e ences a he
subu ban scale migh signi ican ly inc ease he numbe o cooling deg ee hou s and
hus, he ulne abili y owa ds summe ene gy po e y. The U ban Hea Island
(UHI) in ensi y is he di e ence be ween each dis ic ’s empe a u e and Mad id’s
ci y a e age (15.5 ºC) [64].
The HER index is calcula ed as ollows:
A i s , he nume ical alue o all nine de e mining ac o s is assigned o a deg ee o
se e i y, calcula ed h ough a compa ison o he ac o a he dis ic and ci y le els. The
ollowing alues a e ob ained om he hi d Table in Sánchez-Gue a a Sánchez e al. [64]
s udy:
• No se e i y – alue = 0: Means ha he e is no di e ence be ween he dis ic alue
and he ci y a e age.
• Low deg ee o se e i y – alue = 1: When he dis ic alue is sligh ly wo se han he
ci y le el.
• Medium deg ee o se e i y – alue = 1.5: When he dis ic alue is wo se han he
ci y le el.
• High deg ee o se e i y – alue = 2: When he dis ic alue is much wo se han he
ci y le el.
The e is an excep ion o his ule due o he di e en na u e o one o he indica o s: he
UHI in ensi y. The ule o his indica o is he ollowing:
• No se e i y – alue = 0. When he UHI in ensi y is equal o o below 0ºC, meaning
his dis ic would ha e he same empe a u e as Mad id’s a e age.
• Low deg ee o se e i y – alue = 1. When he UHI in ensi y is be ween 0ºC and 2ºC.
• Medium deg ee o se e i y – Value = 1.5. When he UHI in ensi y is be ween 2ºC
and 4ºC.
• High deg ee o se e i y – Value = 2. When he UHI in ensi y is highe han 4ºC.
Secondly, he inal HER alue is calcula ed by a ibu ing alues o each de e mining ac o .
𝐻𝐸𝑅 = 𝑉𝑎+𝑉𝑏+𝑉𝑐+𝑉𝑑+𝑉𝑒 (14)
• Va is he alue assigned o he indica o ‘Buildings buil be o e 1980’;
• Vb is he alue assigned o he indica o ‘Buildings wi h dilapida ed, bad o de icien
main enance condi ions’.
• Vc is ob ained om he assigned alues ela ed o he indica o s ‘Buildings wi h no
hea ing sys ems’, ‘Buildings wi h no cooling sys ems’ and ‘Buildings wi h elec ic
hea ing sys ems’:
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 37
𝑉𝑐 =( 𝑣1+𝑣2+𝑣3 )
3 (15)
o V1: alue assigned o he indica o ‘Buildings wi h no hea ing sys ems’.
o V2: alue assigned o he indica o ‘Buildings wi h no cooling sys ems’.
o V3: alue assigned o he indica o ‘Buildings wi h elec ic hea ing sys ems’.
• Vd is he alue assigned o he indica o ‘Dwelling su ace by household membe ’.
• Ve is he alue assigned o he indica o ‘U ban Hea Island in ensi y’.
On a la ge scale, Eu ope p esen ed an in e es ing p oposal o iden i y and e adica e ene gy
po e y, se ing as a ounda ion o u u e p ojec s. In Decembe 2016, he Ene gy Po e y
Obse a o y (EPOV) was launched by he Eu opean Commission wi h he objec i e o
moni o ing and add essing ene gy po e y h oughou he Eu opean Union membe s a es
[52].
The Obse a o y p o ides a ange o esou ces, da a, and insigh s ela ed o ene gy po e y
[52]:
- Na ional Indica o s Dashboa d: I o e s he la es o icial da a on ene gy po e y
ac oss Eu opean coun ies.
- Publica ions Da abase: A collec ion o epo s, s udies, and case s udies ha
analyse he bes p ac ices and policies aimed a comba ing ene gy po e y.
- Local Indica o s: A a ie y o local indica o s is also p o ided o assis municipali ies
in c ea ing in o med local social clima e plans, acking impac s, and se ing goals
o e ec i e in e en ions.
These esou ces a e designed o p o ide policymake s, esea che s, and s akeholde s wi h
a comp ehensi e ool o unde s and and add ess ene gy po e y e ec i ely ac oss Eu ope.
The EPOV cu en ly has de ined ou p ima y and wen y- ou seconda y indica o s ha can
be used, alone o in combina ion, o de ine ene gy po e y [11] [79] [47]. The p ima y
indica o s a e:
• 2M: Twice he Na ional Median Indica o s
• M/2: Low absolu e ene gy expendi u e
• La e paymen o u ili y bills
• Inabili y o keep he home adequa ely wa m in win e
In a s udy conduc ed by he ‘Cá ed a de Ene gía y Pob eza’ [6], a close look a he o icial
EPOV indica o s and o he s cu en ly being used in o he coun ies is aken, in addi ion o
a classi ica ion o hose as objec i e o subjec i e.
Be o e analysing his s udy, i is impo an o in oduce ano he concep used o classi y
ene gy po e y indica o s: he HEP indica o s. This is pa icula ly ele an , as one o he
objec i e indica o s in oduced la e is speci ically designed o iden i y hidden ene gy
po e y. These indica o s measu e hidden ene gy po e y based on ei he ela i e o
absolu e ene gy expendi u e h esholds. Rela i e indica o s compa e a household’s ene gy

Pàg. 38 Memò ia
spending o he median o a e age expendi u es o simila households wi hin he same
coun y. In con as , absolu e indica o s iden i y households as ene gy poo i hei ac ual
ene gy expendi u es all below hei equi ed o modelled ene gy needs [13].
Objec i e indica o s a e based on quan i iable household da a, such as income and
ene gy expendi u e. These a e u he di ided based on he o m o ene gy po e y hey
assess whe he hey measu e disp opo iona e ene gy expendi u e o insu icien ene gy
expendi u e.
- The disp opo iona e ene gy expendi u e is a household expe iencing ene gy
po e y due o o e spending:
• 10% Indica o : This ea ly me ic iden i ies a household as ene gy poo i i
spends mo e han 10% o i s income on ene gy bills [65]. While i was a
pionee ing app oach, i has no been adop ed by he EPOV due o i s eliance
on a ixed h eshold. By se ing ene gy po e y a a s ic 10% o income, he
measu e isks misclassi ying high-income households ha spend hea ily on
ene gy as ene gy poo [6].
• 2M Indica o : A household is conside ed ene gy poo i i spends mo e han
wice he na ional median on ene gy. Unlike he 10% indica o , his one uses a
ela i e and dynamic h eshold. I is o icially ecognized by he EPOV and
included in ENPE.
• LIHC (Low Income, High Cos ): P oposed in he UK o add ess he
sho comings o he 10% indica o , his measu e iden i ies ene gy po e y when
a household's income (a e ene gy cos s) is below 60% o he na ional median,
and i s ene gy expendi u e is abo e he na ional median. While in luen ial in he
UK, i has no been o icially adop ed by he EPOV.
• LILEE (Low Income, Low Ene gy E iciency): This is he cu en o icial me ic
in England. A household is uel poo i i has low ene gy e iciency ( a ed D o
lowe ) hough obus in design, i is no pa o he EPOV’s selec ed indica o s
as i doesn’ assess ene gy po e y bu assesses uel po e y [40].
• MIS (Minimum Income S anda d): This indica o conside s a household o be
ene gy poo i high ene gy cos s o ce i o o go o he basic needs. I o e s a
p omising accu a e measu e o ene gy po e y i add esses he p oblem om
i s e y economic oo : he income a ailable o ene gy needs a e he basic
needs ha e been me . Un o una ely, i also p esen s a echnical di icul y: he
de e mina ion o he minimum income on an objec i e basis [18].
- The insu icien ene gy expendi u e is a household expe iencing ene gy po e y
due o no mee ing basic needs:
• M/2 Indica o : A household is conside ed ene gy poo i i spends less han hal
o he na ional median on ene gy. I has been o icially ecognized by bo h he
EPOV and he ENPE, conside ed as a ela i e HEP indica o , bu is c i icized
o igno ing income le els, which may lead o misclassi ica ion o non- ulne able
households.
• HEP (Hidden Ene gy Po e y) de eloped by “Cá ed a de Ene gía y
Pob eza de la Uni e sidad Pon i icia Comillas”: This HEP indica o imp o es
upon M/2 by using a heo e ical ene gy expendi u e model and applying an
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 39
income il e o exclude highe -income households. While mo e p ecise, i is no
o icially ecognized by he EPOV.
Subjec i e indica o s ely on households’ sel - epo ed expe iences, ypically collec ed
h ough su eys. They cap u e less isible aspec s o ene gy po e y, such as discom o
o economic s ess, no e lec ed in expendi u e da a.
• La e paymen o u ili y bills: Based on whe he a household epo s being la e on
basic u ili y bill paymen s in he pas 12 mon hs. This is a subjec i e indica o
o icially ecognized by he EPOV.
• Inabili y o keep home adequa ely wa m in win e : This indica o is based on
whe he he household epo s being unable o main ain a com o able indoo
empe a u e du ing he win e mon hs. The EPOV also ecognizes his indica o . In
2023, he measu emen was expanded wi h addi ional ques ions abou he mal
com o in win e and summe .
To sum up his s udy [6], Table 3 is p esen ed o ge a g aphical isualiza ion o which
indica o s a e o icial and which kind o indica o s a e:
Indica o
O icial
EPOV
Objec i e
Disp opo ioned
10%
X
2M
✓
LIHC
X
LILEE
X
MIS
X
Insu icien
M/2
✓
HEP
X
Subjec i e
La e paymen o u ili y bills
✓
Inabili y o keep he home adequa ely wa m in win e
✓
Table 4. Classi ica ion o ene gy po e y indica o s acco ding o hei ype and o icial
s a e in he EPOV [6]
T adi ionally, mos s udies on ene gy po e y ocused on he hea ing consump ion du ing
win e .
Pàg. 40 Memò ia
He nandez-C uz e al. [32] p oposed an inno a i e s a egy o gua an ee a minimum indoo
empe a u e in social housing, an essen ial aspec in con ex s whe e win e condi ions can
pose se ious heal h isks o ulne able indi iduals.
Realini e al. [11] in oduced in hei pape on he p oblem o Ho Homes he "EPi" indica o .
This indica o o e ed an app oach in he sense o “Low Income High Cos s” (LIHC)
indica o s, whe e he a io be ween ene gy expenses and household income (o , in he
I alian case, he a e age mon hly expenses o he household, since he ew s a is ics abou
income canno be ela ed o ene gy expendi u es) is compa ed o a s a is ically de e mined
h eshold o assess whe he a subjec is in an ene gy po e y si ua ion o no .
Howe e , wi h he ongoing inc ease in global empe a u es, cooling needs a e beginning o
ake on a cen al ole. In I aly, nume ous s udies ha e been conduc ed. As p e iously
men ioned, he s udy by Ma acchini e al. [45] showed a d as ic inc ease in ene gy
consump ion du ing hea wa es. Simila ly, Vu o e al. [75] analysed he impac o clima e
change on ene gy consump ion in public housing in Ba i, iden i ying a co ela ion be ween
he occupan s' age and ene gy consump ion, and highligh ing speci ic ulne abili y pa e ns.
A ound he wo ld, se e al s udies ha e also been ca ied ou , pa icula ly in Sou h Ame ican
and A ican coun ies. Those s udies usually analyse a building o a se o dwellings in
economically ulne able neighbou hoods wi h wa m clima es.
In Ecuado , Gu ié ez e al. [30] employed ene gy simula ions o assess he he mal
beha iou o a social housing om he Ecuado ian p og am “Casa pa a Todos” ac oss ou
ci ies up o he yea 2050, aiming o educe ene gy po e y.
In Mon e ideo, he s udy by Pe ei a-Ruchansky and Pé ez-Fa gallo [54] emphasized he
impo ance o passi e design in imp o ing he mal com o in social housing.
In Pe u, Gu ie ez and de Angelis [31] compa ed low-cos passi e s a egies in u al
housing o comba ene gy po e y, p oposing in e en ions adap ed o simila clima es.
A e all his esea ch, one key obse a ion is he absence o an indica o capable o
iden i ying o classi ying a dwelling a ec ed by ene gy po e y based solely on building
cha ac e is ics, such as i s s uc u e, ma e ials, o in e nal loads.
In Spain, he only ool ha pa ially add esses his is he building ene gy ce i ica ion
sys em, egula ed by he Código Técnico de la Edi icación (CTE). This ce i ica ion assigns
an ene gy label o buildings anging om A (mos e icien ) o G (leas e icien ). Howe e ,
his ce i ica ion assesses only he heo e ical ene gy demand and e iciency o a building,
wi hou accoun ing o ac ual ene gy consump ion, household beha iou , o socio-
economic condi ions. While i can se e as a use ul echnical e e ence, pa icula ly when
combined wi h household income and expendi u e da a, i is insu icien as a s andalone
indica o o ene gy po e y. I becomes meaning ul in composi e indica o s such as LILEE,
which aim o iden i y ene gy-poo households by co ela ing ene gy pe o mance wi h
income da a.
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 41
Al hough he ene gy ce i ica ion can highligh dwellings wi h high ulne abili y po en ial,
such as hose a ed E, F, o G, i canno independen ly de e mine ene gy po e y. A
dwelling wi h a high e iciency a ing (A, B, o C) may s ill house a amily ha canno a o d
o main ain adequa e he mal com o due o low income. Con e sely, a poo ly a ed
building may be occupied by indi iduals who can a o d ene gy cos s and hus a e no in a
s a e o ene gy po e y.
Pàg. 48 Memò ia
Fig 3. Su ounding buildings o he building s udied, CM
This o ien a ion poses po en ial he mal com o challenges. Sou hwes - acing açades a e
pa icula ly ulne able o excessi e sola gains du ing la e summe a e noons— he ho es
pe iod o he day. As a esul , in e io spaces acing his di ec ion a e p one o o e hea ing,
he eby inc easing he cooling demand. Addi ionally, i windows on his açade a e
unshaded o poo ly insula ed, he p oblem is u he exace ba ed, con ibu ing o he mal
discom o and highe ene gy use.
The geome y o he building analysed in his s udy is based on he ypological classi ica ion
o h ee p ima y ypologies p e iously es ablished by Ra e lla e al. [57]:
• Linea blocks wi h g ound loo +5 o +6 loo s: These a e he mos common,
comp ising app oxima ely 85% o he buildings, al hough hey accoun o jus o e
60% o he o al housing uni s. These buildings exhibi minimal a ia ion in loo
plans, ypically ea u ing wo dwellings pe landing. Va ia ions a e limi ed o he
wid h and con igu a ion o laund y spaces, and he p esence o absence o
balconies.
• Towe blocks wi h g ound loo +10 o +6 loo s: Excluding h ee unique owe
ypologies, each ep esen ed by a single building, his ype cons i u es nea ly 10%
o he buildings and accommoda es mo e han 24% o he housing uni s.
• Double linea H-blocks wi h g ound loo +8 loo s: Al hough his ypology
ep esen s only 4.8% o he buildings, i includes mo e han 10% o he dwellings in
he neighbo hood.

Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 49
Fig 4. Linea block building s uc u e (le s uc u e) and double linea H-block building
s uc u e ( igh s uc u e) [57]
Based on he p e iously es ablished classi ica ion, he building selec ed o simula ion in
his s udy co esponds o he i s ypology, due o i s widesp ead p esence and i s
ep esen a i e na u e o ypical low-income households in he a ea. This ypology e e s o
linea blocks cons uc ed a ound 1960, du ing a pe iod when no o mal echnical building
code was in place.
The mos common con igu a ion is a six-s o ey building plus g ound loo , wi hou an
ele a o . The chosen block o ms pa o a se ies o ou consecu i e buildings, all sha ing
he same s uc u al design. Each loo , including he g ound le el, con ains wo apa men s
acing each o he , esul ing in a pu ely esiden ial s uc u e wi hou any comme cial uni s.
The building exhibi s bila e al symme y along bo h he x- and y-axes, indica ing ha he
wo apa men s pe loo a e s uc u ally iden ical. Each uni has an app oxima e a ea o 50
m² and includes h ee double bed ooms, a ki chen, a ba h oom, and a es oom.
Pàg. 50 Memò ia
Fig 5. View o he sou h and wes açade o he building model in Open S udio
The ow o blocks is sepa a ed by app oxima ely 18 me e s om o he buildings on he
same s ee . The building is modelled indi idually in he so wa e o simula ion pu poses,
ep esen ing jus one o he ou iden ical blocks. Howe e , addi ional cons ain s a e
in oduced o eplica e a mo e ealis ic u ban se ing. The model si ua es he building wi hin
10-me e -wide s ee s, lanked by buildings o he same ypology on bo h sides as shown
in Figu e 6. Fu he mo e, he e ain is modelled wi h a 15-me e ele a ion gain along he
main (sou h- acing) açade and a 15-me e descen on he ea (no h- acing) açade,
accu a ely e lec ing he opog aphy o Ciu a Me idiana.
To assess he impac o ising empe a u es and he pe o mance o a ious cooling
s a egies, he building is subdi ided in o 18 he mal zones. These include one en ance
zone, i e s ai well zones, and wel e apa men s, wi h each apa men ea ed as an
indi idual he mal zone o he sake o simpli ica ion. The zones a e g ouped in o wo
unc ional ca ego ies: apa men s and s ai s ( he en ance is included in he s ai s space
ype)
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 51
Fig 6. View o he di e en he mal zones in he building model in Open S udio
Each zone has dis inc dimensions, ma e ials, load cha ac e is ics, and schedules. These
de ails a e ou lined in he ollowing Tables 5 and 6.
Floo A ea [𝒎2]
Volume [𝒎3 ]
Uni
Floo
To al
Uni
Floo
To al
Apa men s
50.53
101.06
606.34
151.58
303,16
1818,96
S ai s
6.63
6.63
39.78
19.89
19.89
119.34
To al
-
107.69
646.12
503,05
1938,3
Table 5. Floo a ea and space olume
Cons uc i e elemen ’s su ace [𝒎2 ]
To al
Sou h
Wes
Eas
No h
Wall A ea
670.32
270.72
128.88
0
270.72
Window
A ea
144.25
70.33
13.8
0
60.12
Roo A ea
107.69
-
-
-
-
Table 6. Window and oo a ea
Pàg. 52 Memò ia
The cha ac e is ics o he cons uc ion elemen s ha e been de i ed om a p e ious s udy
on common building ypologies in Ca alonia, using local egula ions as a e e ence o
selec ing alues ela ed o he mal esis ance, he mal ansmi ance, and he mal
conduc i i y, as well as he densi y and hickness o he cons i uen ma e ials [8] [11].
The mal conduc i i y alues om he classi ica ion abo e ha e been compa ed wi h hose
p o ided by he Cype p og am [24], a s uc u al design and calcula ion so wa e used in
ci il enginee ing and a chi ec u e o pe o m s uc u al designs, elec ical ins alla ions and
ene gy ce i ica es. The alues p o ided by he Cype so wa e a e based on he UNE EN
ISO 6946:2012 s anda d [35], a mo e ecen and comp ehensi e documen ega ding he
calcula ion o he mal esis ance o a ious ma e ials and cons uc ion elemen s. In se e al
cases, he o iginal alues we e adjus ed o align wi h hose used by Cype.
The s uc u e and ma e ials o he cons uc ion elemen s adhe e o he guidelines de ined
o ypologies F/G in he p e iously men ioned s udy [8]. This choice is based on he indings
o Ra e lla e al. [57], which s a ed ha he mos common esiden ial buildings in he
neighbo hood we e cons uc ed be ween 1950 and 1960, ypically consis ing o six loo s
wi h wo apa men s pe loo . This desc ip ion co esponds wi h ypology F/G as ou lined
in Annex 2 o he s udy [8].
A summa y o he he mal conduc i i y and densi y o each cons uc i e elemen is
p o ided in Table 7.
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 53
Cons uc i e
elemen
Ma e ial
Thickness
Densi y
The mal
conduc i i y
The mal
Resis ance
The mal
ansmi ance
Uni s
[m]
[𝑘𝑔 𝑚3
⁄]
[𝑊𝑚 ·𝐾
⁄]
[𝑚2·𝐾 𝑊
⁄]
[𝑊𝑚2·𝐾
⁄]
Ex e io walls
Lime
mo a
0.02
1125
1.3
0.01538
1.7809
Ce amic
b ick
0.14
825
0.7
0.2714
Ai
chambe
0.1
-
-
0.19
Ce amic
b ick
0.05
825
0.7
0.0714
Gypsum
mo a
0.02
1600
1.5
0.01333
Wall in
be ween
buildings
Cemen
mo a
0.02
1800
1.7
0.01176
3.37
Ce amic
b ick
0.14
825
0.7
0.2714
Gypsum
mo a
0.02
1600
1.5
0.01333
In e nal walls
Gypsum
mo a
0.02
1600
1.5
0.01333
4.4119
Ce amic
b ick
0.05
825
0.7
0.2
Gypsum
mo a
0.02
1600
1.5
0.01333
In e io loo s
Gypsum
mo a
0.02
1600
1.5
0.01333
2,407
Hollow
slab
0.3
1240
0.8
0.375
Cemen
mo a
0.02
1800
1.7
0.01176
In e io
loo ing
0.02
2300
1.3
0.01538

Pàg. 54 Memò ia
Floo in
con ac wi h
he g ound
In e io
loo ing
0.02
2300
1.3
0.01538
3.96
Cemen
mo a
0.02
1800
1.7
0.01176
Conc e e
0.2
2243
1.7296
0.225
Windows
Simple
window
glass
0.004
2500
0.016
0.25
4.1
Ex e io doo
Me al
s uc u e
0.0008
7824
50
0.000016
62.5
Ceilings
In e io
loo ing
0.02
2300
1.3
0.01538
2.407
Cemen
mo a
0.02
1800
1.7
0.01176
Hollow
slab
0.3
1240
0.8
0.375
Gypsum
mo a
0.02
1600
1.5
0.01333
Roo
Ex e io
loo ing
0.03
2300
1.7
0.01764
2.225
Ce amic
chain
0.05
1800
1.15
0.04347
Hollow
slab
0.3
1240
0.8
0.375
Gypsum
mo a
0.02
1600
1.5
0.01333
Table 7. Table o pa ame e s o each cons uc i e elemen .
4.2.3. Loads and schedules
Schedules and in e nal loads can be de ined in OpenS udio o a ious he mal zones and
space ypes. In his hesis, hese pa ame e s ha e been p ima ily es ablished by se e al
s anda ds and guidelines commonly applied in p e ious s udies on esilien cooling in
buildings, as well as hose issued by Spain’s S anda diza ion O ganiza ion (UNE) [70] [71]
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 55
[72] [10]. Howe e , ce ain pa ame e s ha e been adap ed o e lec condi ions associa ed
wi h ene gy po e y in esiden ial buildings, based on indings om a ious s udies
add essing he mal com o in esiden ial condi ions like his ype o housing.
Occupancy alues om p e ious s udies [70] [46] [51] [48] we e gene ally se a 3 pe sons
pe apa men and 1 pe son in he s ai well, based on UNE EN 16798-1:2020 [71], which
egula es occupancy a 28.3 m²/pe son o esiden ial spaces and 17.0 m²/pe son o
common a eas such as s ai s. Howe e , based on he indings o Ra e lla e al. [37]
[57],occupancy le els in he Ciu a Me idiana neighbo hood a e ypically highe due o he
socioeconomic condi ions o i s esiden s. I is common o ind amilies o 4 o 5 membe s
li ing in each apa men , and no uncommon o ind g oups o 5 o 6 un ela ed indi iduals
sha ing a uni .
The le el o physical ac i i y assumed o occupan s in esiden ial spaces is low o medium,
co esponding o a me abolic a e o app oxima ely 100–150 W/pe son. Fo common
ci cula ion a eas such as en ances and s ai wells, highe ac i i y le els a e assumed, wi h
a a e o 180 W/pe son. These alues a e based on UNE-EN ISO 7730:2006 and UNE-EN
ISO 8996:2021 [72] [10].
. Fig 10. Occupancy schedules o apa men s and s ai s
0
0,2
0,4
0,6
0,8
1
1,2
012345678910 11 12 13 14 15 16 17 18 19 20 21 22 23
Occupancy schedules
Occupancy Apa men s Occupancy S ai s
Pàg. 56 Memò ia
Fig 11. Ac i i y schedules o apa men s and s ai s
In il a ion a es and in e nal elec ical loads a e es ablished acco ding o UNE EN 16798-
1:2020 [71] [16]. In il a ion is se a 0.5 L/s·m² o esiden ial uni s.
Elec ical equipmen loads a e de ined as 3 W/m² o apa men s and 1 W/m² o en ances
and s ai wells.
Rega ding ligh ing, he in e io ligh ing load is limi ed o 1 W/m² ac oss all spaces
(apa men s, en ances, and s ai wells) in compliance wi h he Spanish Building Code DB
HE 2019 [42].
Fig 12. Ligh s schedules o apa men s and s ai s
0
20
40
60
80
100
120
140
160
180
200
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Ac i i y schedules
Ac i i y Apa men s S ai s Apa men s
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Ligh schedules
Ligh s Apa men s Ligh s S ai s
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 57
Fig 13. Elec ical equipmen schedules o apa men s and s ai s
Schedules a e in oduced in he so wa e as amoun pe uni o elemen . Fo example, when
occupancy is se o 0.5, i means ha hal o he people se o belong o a he mal zone will
be he e a ha momen . The load o apa men s is 3 inhabi an s pe each, meaning ha
when he schedule is se o 1, 3 people will be in ha apa men .
Cooling and hea ing schedules, along wi h hei co esponding se poin empe a u es, a e
inco po a ed in o he model. In p e ious s udies [70] [46] [51] [48], hese alues we e
ypically se a 26 °C o cooling du ing he main hou s o ac i i y in apa men s, inc easing
o 28 °C a nigh o educe ene gy demand. Fo hea ing, se poin s we e ixed a 20 °C all
day long, ollowing he ecommenda ions ou lined in UNE-EN 16798-1:2020 [71].
In con as , his s udy adop s a di e en app oach based on he indings o Reallini e al.
[11], which de ined “minimum com o ” condi ions in he con ex o ene gy po e y.
Acco ding o his esea ch, indoo empe a u es should be main ained a a minimum o
18 °C du ing he day and 16 °C a nigh o hea ing, while cooling se poin s should no be
lowe han 28 °C du ing he day and may ise o 30 °C a nigh .
En ance halls and s ai wells a e no he mally condi ioned in his s udy, as hese a eas a e
conside ed o ha e minimal impac on occupan com o due o he limi ed ime spen in
hem. Ne e heless, i is necessa y o assign se poin alues in he simula ion model. To
ensu e ha no ac i e hea ing o cooling sys ems a e igge ed in hese zones, ex eme se
poin s o 60 °C o cooling and 1 °C o hea ing ha e been assigned. These alues
e ec i ely exclude hese spaces om condi ioning in he model. The comple e se poin
schedule alues a e summa ized in Table 8.
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Elec ic equipmen schedules
Ac i i y Apa men s S ai s Apa men s
Pàg. 64 Memò ia
• Indoo O e hea ing Deg ee (IOD)
• Ambien Wa mness Deg ee (AWD)
• O e hea ing Escala ion Fac o (α)
These me ics ha e been applied in p e ious esea ch and a e hus well-sui ed o his
s udy, as hey enable compa a i e analysis wi h exis ing li e a u e i equi ed.
Fo he e alua ion o he mal com o , he ollowing indica o s a e calcula ed o mos cases:
• Hea Index (HI)
• Discom o Index (DI)
• Annual Hou s o Exceedance (HHE o CHE)
These indices p o ide a mo e comp ehensi e unde s anding o indoo en i onmen al
quali y and enhance he alidi y and obus ness o he esul s.
No ene gy po e y indica o was s udied in his wo k, as mos exis ing indica o s ely hea ily
on de ailed economic da a, and he analysis o such economic da a was beyond he scope
o his s udy.

Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 65
5. Resul s
This e alua ion ollows he same me hodology p oposed in p io s udies [70] [68]. Be o e
e alua ing he impac o esilien cooling echnologies on he modelled building, i is
necessa y o assess i s ini ial he mal pe o mance, which will se e as he baseline o
upcoming compa isons. A e wa ds, each cooling echnology will be indi idually analysed
o de e mine how i a ec s he building’s esilience compa ed o he base case. Addi ionally,
a scena io combining all cooling echnologies is simula ed and examined wi h he same
objec i e: o e alua e imp o emen s in esilience. Finally, he esul s ob ained om his
building a e compa ed o hose o a sepa a e s udy [43] ha assessed he esilience o he
mos ep esen a i e dwelling ype in Ca alonia, also modelled unde Ba celona's clima e
condi ions.
5.1. Resilience analysis base case
This sec ion p esen s he analysis o he base case (OG), which e e s o he building
wi hou any implemen ed cooling echnologies. The e alua ion is based on he g aphical
esul s ob ained om esilience and he mal com o indica o s. The s udy is conduc ed o
h ee di e en pe iods: p esen (P), mid- u u e (MF) and long u u e (LF). Fo each o hese
ime ames, wo me eo ological condi ions a e examined: a Typical Me eo ological Yea
(TMY) and ex eme hea e en s, commonly e e ed o as Hea wa es (HW).
The calcula ions pe o med by Ene gyPlus allow us o de e mine he alues o he indica o s
o he en i e building and each o i s he mal zones. All g aphs included in his sec ion ha e
been gene a ed using he Py hon sc ip s de eloped by Baucells e al. [71].
5.1.1. Resilience analysis
The i s analysis ocuses on e alua ing he esilience o he base case (OG). The ini ial
s ep in ol es s udying he gene al pa ame e α.
Fig 16. Alpha (OG) in TMY Long- u u e, Mid-Fu u e and P esen
Pàg. 66 Memò ia
Fig 17. Alpha (OG) in he di e en HW ( om Long- u u e o P esen (le o igh ))
The pa ame e α ep esen s he building's esis ance o inc easing ou doo empe a u es.
A lowe α alue signi ies g ea e esilience o he impac s o clima e change. I he isk o
indoo o e hea ing emains low despi e high ou doo ai empe a u es, he alpha alue will
emain low. As obse ed in Figu es 16 and 17, he a e age α ac oss he building du ing
bo h he Typical Me eo ological Yea (TMY) and hea wa e (HW) scena ios ne e exceeds
a alue o 1.
An alpha alue abo e 1 indica es ha he building is unable o e ec i ely mi iga e he e ec s
o clima e change. In such cases, indoo condi ions may become compa able o o wo se
han ou doo condi ions in e ms o heal h isk. In his s udy, he building consis en ly
main ains α alues below 1, sugges ing i is gene ally capable o coun e ac ing he ad e se
e ec s o clima e change on indoo empe a u es. Howe e , α ne e alls below 0.73,
implying ha he building's abili y o p o ec i s occupan s om clima e- ela ed he mal s ess
is mode a e, a he han op imal.
Le ’s ake a close look now o he alpha pa ame e ac oss indi idual in e io spaces,
Figu es18 and 19, o iden i y he he mal zone wi h he poo es pe o mance.
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 67
Fig 18. Alpha o each he mal zone (OG) in TMY Long- u u e, Mid-Fu u e and P esen
Fig 19. Alpha o each he mal zone (OG) in he di e en HW ( om Long- u u e o P esen
(le o igh ))
F om a mo e accu a e pe spec i e, whe e all he he mal zones a e s udied indi idually, he
alpha dis ibu ion map e eals ha in ce ain zones, alpha exceeds 1. This phenomenon is
p ima ily obse ed du ing p esen -day hea wa es (HW_P) and unde u u e clima e
scena ios p ojec ed (TMY_LF). A p elimina y e iew o he Figu es 18 and 19 indica es ha
Apa men 6 L demons a es he poo es he mal pe o mance, wi h α alues anging om
0.89 o 1.11 h oughou he yea . Con e sely, Apa men 1R exhibi s he bes he mal
Pàg. 68 Memò ia
pe o mance, wi h alpha alues be ween 0.0844 and 0.1784.
Du ing he mos p olonged, in ense, and se e e cu en hea wa es, alpha alues a e
no ably high in apa men s loca ed on he 4 h and 5 h loo s, eaching alues up o 1.03.
To be e in e p e he ob ained alpha alues, we examine he wo indica o s used in i s
calcula ion: IOD and AWD.
Fig 20. AWD (OG) in TMY Long- u u e, Mid-Fu u e and P esen
Fig 21. AWD (OG) in he di e en HW ( om Long- u u e o P esen (le o igh ))
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 69
Fig 22. IOD (OG) o each he mal space in TMY Long- u u e, Mid-Fu u e and P esen
Fig 23. IOD (OG) o each he mal space in he di e en HW ( om Long- u u e o P esen
(le o igh ))
The IOD indica o is pa icula ly high in apa men s om he second loo upwa ds, as seen
in Figu es 22 and 23, wi h he maximum alue eco ded a 12.95 du ing he longes and
mos se e e hea wa e in he long- e m u u e (HM_LF_LMS). Addi ionally, he IOD alues
in Figu e 23 shows ha he s ai wells on he 4 h o 6 h loo s expe ience he highes alues.
This can be a ibu ed o hei sou he n o ien a ion and he p esence o ixed windows on
he sou h- acing su aces. Since hese windows canno be opened, ai exchange is minimal,
esul ing in an ele a ed isk o indoo o e hea ing in hese a eas.

Pàg. 70 Memò ia
Figu es 20 and 21 display he AWD alue, and as expec ed, he Ambien Wa mness in he
TMY_LF inc eases by 69.47% compa ed o i s ini ial alue in TMY_P, ising om 7.47 o
12.66.
5.1.2. Com o analysis
The Hea Index (HI) is he i s com o indica o e alua ed. I ep esen s he appa en
empe a u e el by he human body when ai empe a u e is combined wi h ela i e humidi y
[77]. This index is widely used o assess he le el o isk associa ed wi h exposu e o ac ual
ambien empe a u es [29].
Fig 24. HI (OG) in TMY Long- u u e, Mid-Fu u e and P esen
Fig 25. HI (OG) in he di e en HW ( om Long- u u e o P esen (le o igh ))
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 71
The esul s o Figu es 24 and 25 indica e ha , o e ime, he p opo ion o occupied hou s
ca ego ized unde he Cau ion le el will signi ican ly decline in he long u u e. Speci ically,
his le el accoun s o only 17.2% o occupied hou s in he p esen (P) and 19.02% in he
mid- u u e (MF). In he long u u e (LF), nea ly hal o all occupied hou s will all unde he
Ex eme Cau ion ca ego y, wi h 0.32% eaching he Ex eme Dange le el. Condi ions
wo sen conside ably du ing hea wa es: in he mos p olonged and in ense p esen -day
e en s, a maximum o 14.88% o occupied hou s all wi hin he Cau ion le el, while he
emaining hou s all wi hin he Ex eme Cau ion ca ego y. In long- u u e hea wa e
scena ios, be ween 79.17% and 91.25% o occupied hou s a e classi ied unde he Dange
le el, wi h 1.39% eaching Ex eme Dange .
As hese HI alues ep esen a e ages ac oss he en i e building, and conside ing he
he e ogenei y in he mal pe o mance be ween di e en spaces, we now compa e
Apa men s 1R and 6L, Figu es 26 and 27, which ha e demons a ed he bes and wo s
he mal pe o mance, espec i ely.
Fig 26 and 27. HI (OG) alues o e e y TMY pe iod o Apa men 1 R and 6 L
Unde he Typical Me eo ological Yea scena io, no able di e ences eme ge be ween
g ound- loo apa men s and hose on highe le els. Fo ins ance, esiden s o i s - loo
uni s adjacen o neighbou ing buildings bene i om be e he mal insula ion and
p o ec ion. In con as , uni s such as Apa men 6L (Figu e 27), loca ed on he op loo wi h
di ec wes - acing sola exposu e, expe ience a mo e in ense hea condi ions. On he i s
loo , sa e HI condi ions can s ill be obse ed e en in long- u u e scena ios (Figu e 28);
howe e , his is no he case on he six h loo (Figu e 29).
Pàg. 72 Memò ia
Fig 28. HI (OG) alues o e e y HW ( om Long- u u e o P esen (le o igh )) o
Apa men 1 R
Fig 29. HI (OG) alues o e e y HW ( om Long- u u e o P esen (le o igh )) o
Apa men 6 L
The second indica o examined is he Discom o Index (DI), which es ima es he
pe cen age o occupied hou s du ing which esiden s expe ience he mal discom o due o
hea .
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 73
Fig 30. DI (OG) in TMY Long- u u e, Mid-Fu u e and P esen
Fig 31. DI (OG) in he di e en HW ( om Long- u u e o P esen (le o igh ))
Analysis o his index (Figu es 30 and 31) e eals ha , e en in he p esen , signi ican
he mal discom o is al eady occu ing, wi h se e e hea condi ions a ec ing 3.31% o
occupied hou s, as seen in Figu e 30. This DI alue inc eases sha ply o 59.19% in he
long- u u e scena io. Du ing hea wa es in long- u u e condi ions (Figu e 31), se e e
discom o is expec ed du ing 87.5% o 96.63% o all occupied hou s.
Pàg. 80 Memò ia
be ween Apa men s 1 R and 6 L.
In he p esen (P), he wa mes day is Augus 12, wi h an ou doo empe a u e o 35.5ºC a
16:00. Inside Apa men 1R (Figu e 40), he empe a u e on ha same day is he highes o
he yea , 27.3ºC. In con as , inside Apa men 6L (Figu e 41), he empe a u e on ha same
day is 34.24ºC, hough i is no he wa mes day; ha occu s on June 25, wi h a peak o
36ºC.
In he mid- u u e (MF), he wa mes day is July 25, wi h an ou doo empe a u e o 34.9ºC
a 15:00. Inside Apa men 1R (Figu e 42), he empe a u e on ha day is again he highes
o he yea , 28.3ºC. Meanwhile, in Apa men 6L, he empe a u e is 34.24ºC, bu his is no
he ho es day ei he ; ha again alls on June 25, eaching 36ºC (Figu e 43)
In he long- u u e (LF), he wa mes day is July 24, wi h an ou doo empe a u e o 43.6ºC
a 15:00. This is also he wa mes indoo day o he yea in bo h apa men s. In Apa men
1R (Figu e 44), he indoo empe a u e eaches 29.96ºC. In con as , Apa men 6L eco ds
39.91ºC on he same day, al hough i s highes empe a u e occu s on Augus 10, eaching
40.1ºC (Figu e 45).
5.2. Resilience analysis wi h cooling echnologies
This sec ion ocuses on how he selec ed cooling echnologies in luence he building’s
esilience. Each cooling s a egy will be analysed sepa a ely, ollowed by hei combined
e ec , and inally, a compa ison will be made wi h he base case esul s. Compa ing all
simula ed echnologies is essen ial o iden i y he mos e ec i e solu ions in esponse o
clima e a ia ion. Fo cla i y, he analysis is di ided in o wo pa s: Typical Me eo ological
Yea (TMY) and Hea wa es (HW).
The i s s ep is o assess he ene gy use o he base case (OG) e sus he building
equipped wi h addi ional cooling echnologies: Na u al Ven ila ion (NV), Blinds (BL), and
hei combina ion (NV_BL). I ’s impo an o no e ha all cooling echnologies analysed in
his s udy a e passi e s a egies, meaning hey do no esul in any addi ional ene gy
consump ion.
5.2.1. TMY Analysis
S udying he e ec o cooling echnologies du ing he mos ypical me eo ological yea s o
he p esen , mid- u u e, and long- u u e o e s insigh in o he building’s esponse o ising
empe a u es due o clima e change.
5.2.1.1. Resilience s udy
To begin he analysis, we obse e how he alpha indica o esponds o each cooling

Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 81
s a egy and i s combina ions. We will examine esul s o h ee cooling s a egies: Na u al
Ven ila ion (NV), Blinds (BL) and Na u al Ven ila ion combined wi h Blinds (NV_BL).
Fig 46. Alpha wi h cooling echnologies du ing TMY
F om Figu e 46, we see ha o each cooling s a egy, he alpha alue inc eases o e ime,
and a p edic able ou come gi en he s ong impac o clima e change in he long- u u e
scena io. Among he s a egies, na u al en ila ion alone p o ides he g ea es
imp o emen in Alpha, al hough no consis en ly ac oss all ime pe iods. In he p esen , wi h
lowe ou doo empe a u es, na u al en ila ion wo ks well o e esh indoo ai and main ain
he mal com o . Howe e , as ou doo empe a u es ise in he u u e, i s e ec i eness
signi ican ly diminishes, causing he alpha alue o mo e han double, om 0.29 o 0.7.
O e all, he bes pe o mance is obse ed when combining bo h echnologies (NV_BL),
hough e en his combina ion sees a subs an ial d op in e ec i eness in he long u u e due
o ex eme hea .
5.2.1.2. Com o s udy
The HI and DI indica o s p o ide insigh in o he he mal com o expe ienced by esiden s.
The alues p esen ed ep esen he a e age pe apa men ac oss he building.
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
OG NV BL NV_BL
Alpha (α) pe cooling echnology/TMY pe iods
TMY_P TMY_MF TMY_LF
Pàg. 82 Memò ia
Fig 47. HI wi h cooling echnologies du ing TMY
Fo he HI in Figu e 47, dange and ex eme dange le els a e absen in he p esen .
Howe e , hese pe cen ages inc ease signi ican ly o e ime. The bes HI alues a e
ob ained wi h he combina ion o na u al en ila ion and blinds, while using blinds alone
p oduces he leas a ou able esul s.
0
10
20
30
40
50
60
70
80
90
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
TMY_P TMY_MF TMY_LF
DI pe cooling echnology/TMY pe iods in he building
OG NV BL NV_BL
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 83
Fig 48. DI wi h cooling echnologies du ing TMY
The DI esul s in Figu e 48 e lec s he pe cei ed discom o due o hea and humidi y,
exp essed as a pe cen age o occupied hou s. In he long u u e, ex eme condi ions o
se e e hea a e eco ded, leading o highly un a ou able DI alues. E en wi h he
implemen a ion o na u al en ila ion o i s combina ion wi h blinds, he esul s emain
inadequa e. A s i ling and uncom o able indoo en i onmen is an icipa ed unde u u e
clima e condi ions.
0
10
20
30
40
50
60
70
80
No hea Mild
hea
Hea y
hea
Se e e
hea
No hea Mild
hea
Hea y
hea
Se e e
hea
No hea Mild
hea
Hea y
hea
Se e e
hea
TMY_P TMY_MF TMY_LF
DI pe each cooling echnology/TMY pe iods
OG NV BL NV_BL
Pàg. 84 Memò ia
Fig 49. HHE wi h cooling echnologies du ing TMY_P
Fig 50. HHE wi h cooling echnologies du ing TMY_MF
0
100
200
300
400
500
600
700
800
900
1000
Apa 1
L
Apa 1
R
Apa 2
L
Apa 2
R
Apa 3
L
Apa 3
R
Apa 4
L
Apa 4
R
Apa 5
L
Apa 5
R
Apa 6
L
Apa 6
R
HHE indica o du ing TMY_P
OG NV BL NV_BL
0
100
200
300
400
500
600
Apa
1 L
Apa
1 R
Apa
2 L
Apa
2 R
Apa
3 L
Apa
3 R
Apa
4 L
Apa
4 R
Apa
5 L
Apa
5 R
Apa
6 L
Apa
6 R
HHE indica o du ing TMY_MF
OG NV BL NV_BL
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 85
Fig 51. HHE wi h cooling echnologies du ing TMY_LF
The inal com o indica o HHE, measu es how many hou s pe yea indoo empe a u es
su pass com o able limi s pe each apa men . In he p esen (Figu e 49), o apa men
spaces, he mos e icien s a egy is NV + BL, while using only blinds is he leas e ec i e,
causing a peak o a ound 932 hou s o ho exceedance in mos o he apa men s abo e
he second loo . In he long u u e (Figu e 51) we can see how no e en he apa men wi h
bes he mal pe o mance, 1 R, ha e a HHE le el lowe han 400 hou s, app oxima ely 50
hou s mo e han hose allowed by his same indica o in he CTE. A no able obse a ion is
he declining pe o mance o he NV + BL combina ion in bo h he mid- and long- u u e
scena ios, whe e he HHE alues o all s a egies con e ge and become simila .
Based on his s udy o he TMY, he op imal cooling s a egy is he combina ion o Na u al
Ven ila ion and Blinds (NV + BL), despi e i s diminishing e ec i eness o e ime.
5.2.2. HW Analysis
Hea wa es ep esen he pe iods when a building’s esilience is mos c i ically es ed.
Howe e , he HW da a e e s o he en i e yea in which he hea wa e occu ed, spanning
om Janua y 1s o Decembe 31s . In his sec ion, we analyse se en di e en hea wa es,
selec ed as he longes , mos in ense, and mos se e e ac oss he h ee ime pe iods
s udied. Th ee a e om he p esen , wo om he mid- u u e, and wo om he long u u e.
Each pe iod is analysed sepa a ely o cla i y and be e unde s anding.
0
100
200
300
400
500
600
700
800
Apa 1
L
Apa 1
R
Apa 2
L
Apa 2
R
Apa 3
L
Apa 3
R
Apa 4
L
Apa 4
R
Apa 5
L
Apa 5
R
Apa 6
L
Apa 6
R
HHE indica o du ing TMY_LF
OG NV BL NV_BL

Pàg. 86 Memò ia
5.2.2.1. Resilience s udy
To assess he building’s esilience, he i s pa ame e conside ed is he alpha.
Fig 52. Alpha wi h cooling echnologies du ing P esen HW (P)
Fig 53. Alpha wi h cooling echnologies du ing Mid- u u e HW (MF)
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
OG NV BL NV_BL
Alpha (α) pe each cooling echnology/ HW p esen
HW_P_MS HW_P_MI HW_P_L
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
OG NV BL NV_BL
Alpha (α) pe each cooling echnology/ HW mid u u e
HW_MF_MIS HW_MF_L
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 87
Fig 54. Alpha wi h cooling echnologies du ing Long- u u e HW (LF)
As p e iously obse ed in Figu e 46, in he TMY esul s, α alues inc ease o e ime. The
mos se e e hea wa es end o yield he highes alpha alues, pa icula ly in he p esen
(Figu e 52) and mid- u u e (Figu e 53). Howe e , in he long u u e (Figu e 54), he wo s
esul s co espond o he longes hea wa e a he han he mos in ense. E en so, na u al
en ila ion combined wi h blinds emains he mos e ec i e passi e s a egy o mi iga ing
ising empe a u es, hough i s e ec i eness signi ican ly d ops in he long e m. In ha
scena io, blinds alone appea o be he only cos -e ec i e passi e solu ion o educing
Alpha and p o ec ing apa men s om sola adia ion. Impo an ly, Alpha ne e exceeds 1
in any pe iod, which is a posi i e sign, indica ing ha while mi iga ion is weak, i is s ill
unc ioning o some ex en .
5.2.2.2. Com o s udy
The ollowing s eps o he analysis a e o obse e he esul s om he HI, DI and HHE index.
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
OG NV BL NV_BL
Alpha (α) pe each cooling echnology/ HW long u u e
HW_LF_MI HW_LF_LMS
Pàg. 88 Memò ia
Fig 55. HI wi h cooling echnologies du ing P esen HW (P)
Fig 56. HI wi h cooling echnologies du ing Mid- u u e HW (MF)
0
10
20
30
40
50
60
70
80
90
100
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
HW_P_MS HW_P_MI HW_P_L
HI pe cooling echnology/HW in he p esen
OG NV BL NV_BL
0
10
20
30
40
50
60
70
80
90
100
Sa e
condi ions
Cau ion Ex em
cau ion
Dange Ex eme
dange
Sa e
condi ions
Cau ion Ex em
cau ion
Dange Ex eme
dange
HW_MF_MIS HW_MF_L
HI pe cooling echnology/HW in he mid u u e
OG NV BL NV_BL
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 89
Fig 57. HI wi h cooling echnologies du ing Long- u u e HW (LF)
The e is minimal di e ence in he HI esul s be ween TMY (Figu e 47) and HW scena ios
(Figu es 55, 56 and 57). In he p esen , Figu e 55, he e a e almos no hou s classi ied as
dange ous, excep in he base case (OG) wi h only 4.75%. Du ing he mid- u u e (Figu e
56), ex eme cau ion hou s begin o ise o 86.31% du ing HW_MF_MIS, and by he long
u u e (Figu e 57), mos occupied hou s all wi hin ex eme cau ion and dange ca ego ies,
achie ing 84.33% du ing HW_LF_LMS. A ew ex eme dange hou s appea , especially in
simula ions o he base case and na u al en ila ion alone.
This ou come con i ms a p e iously discussed p oblem: as ime p og esses, he mal
discom o wo sens, making na u al en ila ion less e ec i e. The ou side ai , which would
ypically help cool he indoo en i onmen , becomes equal o o ho e han indoo ai ,
o e ing li le o no cooling bene i .
0
10
20
30
40
50
60
70
80
90
100
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
HW_LF_MI HW_LF_LMS
HI pe cooling echnology/HW in he long u u e
OG NV BL NV_BL
Pàg. 96 Memò ia
Fig 65. Ma e ials o TY [43]
Bo h buildings we e cons uc ed in he pos Spanish Ci il Wa pe iod, du ing a ime when
he e we e no building egula ions like he Código Técnico de la Edi icación (CTE) in place.
As a esul , cons uc ion we e no specially ocused on ene gy e iciency o he mal com o ,
leading o buildings wi h limi ed he mal pe o mance. While he cons uc ion ma e ials and
he mal p ope ies o bo h buildings a e ela i ely simila , wi h nei he o e ing high-
pe o mance insula ion, he key di e en ia ing ac o lies in he implemen a ion o cooling
echnologies. In he ypical Ca alan building, he use o ac i e cooling sys ems helps
imp o e indoo com o and esilience o clima e change. In con as , he building loca ed in
he mos socioeconomically disad an aged a ea, despi e ha ing compa able cons uc ion,
has mo e di icul ies implemen ing such sys ems due o ene gy po e y.
A mo e speci ic analysis o he esilience o he wo buildings has been ca ied ou . The
indica o s ha ha e been compa ed a e he ones used in he wo s udies: alpha o
esilience and HI and DI o com o .

Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 97
6.1. Resilience analysis, buildings compa ison o he base
cases
A i s , he base case o bo h buildings was compa ed o conclude how he su oundings
and he s uc u e o hese a ec ed he esilience and com o indica o s s udied. Wi h his
in o ma ion, conclusions can be d awn on how he buildings o amilies in a si ua ion o
ene gy po e y beha e owa ds he mos ypical building o Ca alunya, ini ially o amilies
wi hou signi ican inancial p oblems. Subsequen ly, hese da a will be compa ed wi h he
esul s o hese same indica o s bu o buildings wi h applied cooling echnologies. Wi h
his las compa ison, we will be able o see how necessa y cooling echnologies a e o he
com o o he inhabi an s o a building and how hose a ec ed by a si ua ion o ene gy
po e y will eel.
Fig 66. Alpha compa ison du ing TMY be ween CM and TY buildings
Fig 67. Alpha compa ison du ing HW be ween CM and TY buildings
By obse ing Figu es 66 and 67, we can al eady see he di e ence in he esilience o bo h
0,73 0,76 0,74
0,56 0,65 0,66
0
0,2
0,4
0,6
0,8
TMY_P TMY_MF TMY_LF
Alpha compa ison du ing TMY
BC_CM BC_TY
0,77 0,77 0,75 0,75 0,74 0,78 0,74
0,63 0,63 0,61 0,65 0,64 0,71 0,67
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
HW_P_L HW_P_MI HW_P_MS HW_MF_L HW_MF_MIS HW_LF_LMS HW_LF_MI
Alpha compa ison du ing HW
BC_CM BC_TY
Pàg. 98 Memò ia
buildings. Du ing hea wa es and he ypical me eo ological yea , he building wi h he
highes alpha is he one s udied in his pape , he Ciu a Me idiana’s building, being up o
22.2% highe han he TY alues du ing HW and up o 30.04% du ing TMY. These esul s
can be explained by he small di e ence in he building’s ma e ials. CM building was buil
wi h highe he mal ansmi ance ma e ials han he TY building, which sugges s less
insula ion and highe hea loss/gain.
Fig 68. HI compa ison du ing TMY be ween CM and TY buildings
0
10
20
30
40
50
60
70
80
90
100
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
TMY_P TMY_MF TMY_LF
HI compa ison du ing TMY
BC_CM BC_TY
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 99
Fig 69. HI compa ison du ing HW_P be ween CM and TY buildings
0
10
20
30
40
50
60
70
80
90
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
HW_P_L HW_P_MI HW_P_MS
HI compa ison du ing HW_P
BC_CM BC_TY
0
10
20
30
40
50
60
70
80
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
HW_MF_L HW_MF_MIS
HI compa ison du ing HW_MF
BC_CM BC_TY
Pàg. 100 Memò ia
Fig. 70. HI compa ison du ing HW_MF be ween CM and TY buildings
Fig 71. HI compa ison du ing HW_LF be ween CM and TY buildings
By obse ing Figu es 68,69,70 and 71 we can see ha he Hea Index o he CM building
has a mo e ele a ed % o occupied hou s classi ied as wi h he ex em cau ion, dange and
ex em dange le els han he TY building. In Figu e 68, i ’s isible how he TY building only
has a 34.58% o dange ous occupied hou s in he Long u u e while he CM building has,
sinse he e y beginning o he s udy, 3.31% o dange ous occupied hou s du ing he
p esen and 52.8% o dange ous occupied hou s du ing he long u u e. In he longes and
mos se e e hea wa e o he long u u e, Figu e 71, whe e he wo s HI alues a e
ob ained, he CM building, apa om he 1.39% o ex em dange ous occupied hou s, has
93.25% o dange ous occupied hou s while he TY building only has 34.88% o hose.
0
10
20
30
40
50
60
70
80
90
100
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
Sa e condi ions
Cau ion
Ex em cau ion
Dange
Ex eme dange
HW_LF_LMS HW_LF_MI
HI compa ison du ing HW_LF
BC_CM BC_TY
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 101
Fig 72. DI compa ison du ing TMY be ween CM and TY buildings
Fig 73. DI compa ison du ing HW_P be ween CM and TY buildings
0
10
20
30
40
50
60
70
80
No
hea
Mild
hea
Hea y
hea
Se e e
hea
No
hea
Mild
hea
Hea y
hea
Se e e
hea
No
hea
Mild
hea
Hea y
hea
Se e e
hea
TMY_P TMY_MF TMY_LF
DI compa ison du ing TMY
BC_CM BC_TY
0
10
20
30
40
50
60
70
80
90
No
hea
Mild
hea
Hea y
hea
Se e e
hea
No
hea
Mild
hea
Hea y
hea
Se e e
hea
No
hea
Mild
hea
Hea y
hea
Se e e
hea
HW_P_L HW_P_MI HW_P_MS
DI compa ison du ing HW_P
BC_CM BC_TY

Pàg. 102 Memò ia
Fig 74. DI compa ison du ing HW_MF be ween CM and TY buildings
Fig 75. DI compa ison du ing HW_LF be ween CM and TY buildings
Figu es 72,73,74 and 75 show ha he Discom o Index o he CM building has a mo e
ele a ed % o occupied hou s classi ied as wi h hea y hea and se e e hea le els han he
TY building. In Figu e 72, du ing he p esen pe iod, CM building has a highe a e o hea y
0
10
20
30
40
50
60
70
No hea Mild hea Hea y
hea
Se e e
hea
No hea Mild hea Hea y
hea
Se e e
hea
HW_MF_L HW_MF_MIS
DI compa ison du ing HW_MF
BC_CM BC_TY
0
10
20
30
40
50
60
70
80
90
100
No hea Mild hea Hea y
hea
Se e e
hea
No hea Mild hea Hea y
hea
Se e e
hea
HW_LF_LMS HW_LF_MI
DI compa ison du ing HW_LF
BC_CM BC_TY
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 103
hea occupied hou s han TY, ye in he long u u e pe iod his si ua ion is e e sed when
TY hea y hea occupied hou s a e 8.45% highe han h CM hea y hea hou s. In he
longes and mos se e e hea wa e o he long u u e, Figu e 75, whe e he wo s DI alues
a e ob ained, he CM building e e s he si ua ion again wi h 96.03% o se e e hea
occupied hou s e sus he 62.81% se e e hea occupied hou s o he TY building.
6.2. Resilience analysis, buildings compa ison wi h cooling
echnologies implemen ed
As wi h he indica o s, he echnologies ha ha e been compa ed a e hose s udied in bo h
wo ks: Na u al Ven ila ion (NV) and Blinds (BL). The o he echnologies simula ed in he TY
building a e: G een Roo (G R ), Ad anced Windows (AdWind) and Ai Condi iona e (AC).
I should be no ed ha hese cooling echnologies ha e no been applied in his wo k o
se e al easons:
• Bo h he GR and he AdWind a e solu ions ha modi y he building's cons uc ion
elemen s. Today, ehabili a ing a building implies ha his ehabili a ion complies
wi h he CTE, which is much s ic e and mo e speci ic han he egula ions ha
exis ed when he wo buildings s udied in his wo k we e buil . In addi ion,
ehabili a ing a mul i- amily esiden ial building implies ha all neighbou s mus be
able o a o d o pay o his e o m. In he case o he CM building, he aim is o
simula e he si ua ion o a ulne able building in he wo s case, he e o e he
objec i e is o s udy how he building eac s wi hou any echnology ha equi es
money.
• The las echnology p oposed o he TY building is AC. This s a egy has been
disca ded since i is a echnology conside ed ac i e, which implies an ex a
consump ion o ene gy o ope a e [45]. Obse ing he case o he TY building, i can
be seen how he elec ici y consump ion o cool he building is mo e han double he
ini ial consump ion du ing he TMY_LF (123.38 MJ/m² wi h AC s. 58.69 MJ/m²
wi hou AC) [43]. This expense is no accep able in he case o he CM building,
whe e solu ions a e in ended o be s udied ha do no cause ex a expenses o he
enan s.
Pàg. 104 Memò ia
Fig 76 and 77. Elec ici y consump ion wi hou and wi h AC in he TY du ing TMY_LF
Wi h ha being said, i has been decided o compa e he passi e solu ion wi h he bes
esul s ob ained in he CM building, he combina ion o Na u al Ven ila ion (NV) oge he
wi h Blinds (BL), in o de o compa e he buildings in he bes -case scena io possible wi h
he cheapes cooling echnologies. The indica o s s udied a e Alpha o esilience and HI
and DI o com o analysis. The alues o his indica o s o he TY building a e aken om
ano he p e ious s udy o his swelling, whe e all o he possible combina ions o cooling
echnologies a e simula ed and s udied [70].
Fig 78. Alpha compa ison du ing TMY be ween CM and TY buildings wi h NV & BL
0,21
0,43
0,57
0,12
0,22
0,38
TMY_P TMY_MF TMY_LF
0
0,1
0,2
0,3
0,4
0,5
0,6
Alpha compa ison NV&BL du ing TMY
NV & BL_CM NV & BL_TY
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 105
Fig 79. Alpha compa ison du ing HW be ween CM and TY buildings wi h NV & BL
As i s been men ioned be o e, he e ec o a be e en elope and insula ion in he TY
building is wha is causing his small bu no iceable di e ence be ween CM and TY alpha
esul s du ing he TMY. In Figu e 78, du ing he p esen , he alpha alue dec eased 71.23%
o CM and 78.57% o TY, compa ed o he alue o he base case (BC) o each building.
Du ing he mid- u u e, he passi e echnologies lose some o hei e ec i eness, as
e lec ed in he alpha alues which now dec eases 43.4% o CM and 65.15% o TY. Fo
u u e scena ios, we can al eady see he inc easing endency o his indica o , which means
ha in he u u e, he indoo o e hea ing combined wi h he ambien wa mness will wo sen
he esilience o his dwellings. A po en ial inconsis ency has been iden i ied in his s udy
ela ed o he analysis o esilience indica o s du ing hea wa e (HW) pe iods. Speci ically,
Figu e 79 e eals ha he TY building exhibi s poo e pe o mance han he CM building in
e ms o he alpha indica o . This ou come is unexpec ed and aises conce ns, as
h oughou he s udy, he CM building has consis en ly demons a ed lowe esilience
compa ed o he TY building. Such esul s sugges he possibili y o an e o in he da a o
one o he wo buildings. I is pa icula ly puzzling ha he CM building eco ds such low
alpha alues, especially du ing he p esen and mid- u u e scena ios when passi e cooling
s a egies emain ela i ely e ec i e. Fo ins ance, as illus a ed in Figu e 79, he alpha
alue du ing he mid- u u e HW pe iod inc eases by only 4.65%, which appea s
disp opo iona ely low. In con as , he TY building p esen s unusually high alpha alues. In
he p esen HW scena io (Figu e 79), he lowes alpha alue eaches 0.37, mo e han iple
he alue o 0.12 eco ded in he p esen TMY scena io. Simila ly, in he mid- u u e, Figu e
78, he TMY alpha alue o 0.38 inc eases by app oxima ely 50%–52.63%, eaching alues
be ween 0.57 and 0.58 du ing HW pe iods. These disc epancies a e epea ed in he esul s
o he o he indica o s.
0,28 0,31 0,35
0,45 0,45
0,37 0,41
0,48
0,57 0,58
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
HW_P_L HW_P_MI HW_P_MS HW_MF_L HW_MF_MIS
Alpha compa ison NV&BL du ing HW
NV & BL_CM NV & BL_TY
Pàg. 112 Memò ia

7. Planning
This sec ion p esen s he planning o he hesis, as shown in Figu es 89 and 90. The ask name column ou lines an o ganized lis o asks ha needed
o be add essed in o de o achie e he p ojec ’s objec i es. Al hough p ojec planning was a undamen al pa o ensu ing he hesis's success, he
p ocess did no go en i ely as in ended.
Fig 89. Gan ’s diag am 2024
Fig 90. Gan ’s diag am 2025
Du ing he de elopmen o his inal deg ee p ojec , s icking o he ini ial plan p o ed di icul due o a numbe o un o eseen challenges. To begin wi h,
he esea ch on a ious ene gy po e y s udies ook longe han an icipa ed, la gely because he ocus o he in es iga ion was unclea a i s . One o
he majo se backs was he mal unc ion o one o he compu e s in ended o use h oughou he p ojec . Due o i s ou da ed condi ion, he de ice was
unable o un essen ial so wa e such as Ske chUp and he OpenS udio plug-in. As a esul , an al e na i e compu e had o be secu ed in o de o
p oceed wi h he building modelling p ocess. This caused signi ican delays in he o iginal imeline and was a key ac o in eques ing an ex ension o
he p ojec . Las ly, once he new compu e was equipped wi h he necessa y p og ams, designing he building model also ook mo e ime han
expec ed. Addi ional ime was needed o become amilia wi h he so wa e, which in ol ed wa ching se e al YouTube u o ials.
8. Economic assessmen
This sec ion p o ides an e alua ion o he economic cos s associa ed wi h he de elopmen
o his s udy. The analysis is di ided in o wo main ca ego ies. Fi s ly, he cos s ela ed o
he modelling o he building, he simula ion hou s, and he ime de o ed o esea ch and
analysis o esul s a e examined. Secondly, an e alua ion is conduc ed o he expenses
associa ed wi h he ma e ials and so wa e used h oughou he de elopmen o his hesis.
8.1. Cos s o hou s dedica ed
Human esou ce cos s encompass bo h he con ibu ions o he s uden and he supe ising
p o esso . These include hou s spen in mee ings, p ojec supe ision, e alua ion o he
s uden 's wo k, and p oblem-sol ing. The es ima ed cos o hese con ibu ions is 20 €/h.
The cos o elec ici y has been calcula ed as he a e age be ween he elec ici y a es o
he s udio, whe e pa o he wo k was conduc ed, and he o ice, whe e he building
modelling ook place. Ene gy consump ion by compu e s he p ojec was de e mined based
on he ol age and ampe age speci ica ions o he powe adap e s (20V and 3.25A,
espec i ely). These alues we e mul iplied and hen di ided by 1,000 o ob ain he powe
consump ion in kilowa s (kW). This esul was hen mul iplied by a ypical powe usage
e iciency ac o o 0.8 [57]. The o al ene gy consump ion was inally calcula ed by
mul iplying his alue by he o al numbe o hou s dedica ed o he p ojec .
Table 15. Cos o he p ojec , wo ked hou s
Concep
Value
Uni s
€/h
To al €
Resea ch hou s (s uden )
85
h
13
1105
Modelling hou s (s uden )
60
h
13
780
Simula ion hou s (s uden )
120
h
13
1560
Analysis hou s (s uden )
65
h
13
845
P ojec d a ing
70
h
13
910
Dedica ed hou s (p o esso )
40
h
30
1200
Ene gy consumed
56
kWh
0.12
6.7
To al
6406.7 €
Pàg. 116 Memò ia
8.2. Cos s o ma e ials
The so wa e u ilized h oughou he de elopmen o his p ojec was ei he open-sou ce o
a ailable h ough ial e sions, he eby incu ing no di ec inancial cos .
Two compu e s we e employed du ing he cou se o he s udy. The ini ial de ice
expe ienced echnical issues ela ed o i s p ocesso and g aphics ca d, necessi a ing i s
eplacemen wi h a new, unc ional compu e o ensu e he con inui y and quali y o he
wo k.
Concep
Value
Uni s
€ pe uni
To al €
P og am licenses
3
Licenses
0
0
Elec onic
de ices
2
Compu e s
1560 + 2450
4110
To al
4110 €
Table 16. Cos o he p ojec , ma e ial cos s
The o al cos o he p ojec amoun s o 10516.7€.
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 117
9. En i onmen al assessmen
This wo k aims o analyse he he mal esponse o a ulne able building o clima e change
and how his esponse a ies depending on he passi e cooling echnologies applied.
These echnologies a e en i ely passi e [39], meaning hey do no consume addi ional
ene gy o ope a e. The objec i e o his sec ion o he s udy is o assess whe he he
implemen a ion o hese echnologies can con ibu e o educing he building's ene gy
consump ion and hus p omo e a mo e sus ainable cooling model.
The echnologies analysed a e Na u al Ven ila ion and Ex e nal Blinds, and hey ha e
been selec ed o wo main easons:
• The i s is o a oid u he con ibu ing o clima e change. Tables 17 and 18 show
he annual hea ing and cooling ene gy demands o he base case building and he
building wi h he bes cooling echnology simula ed o each o he pe iods s udied.
The objec i e is o assess whe he he mos p omising solu ion can e ec i ely
educe he en i onmen al impac o his building and p omo e mo e sus ainable
p ac ices o o he buildings in simila condi ions.
TMY
Pe iods
Hea ing demand [ 𝒌𝑾𝒉 𝒎𝟐
⁄]
Cooling demand [ 𝒌𝑾𝒉 𝒎𝟐
⁄]
BC
NV_BL
Reduc ion
(%)
BC
NV_BL
Reduc ion
(%)
TMY_P
14.73
4.83
67.19
27.31
19.85
27.32
TMY_MF
11.19
2.38
78.72
38.81
26.72
31.14
TMY_LF
3.09
0.62
80.20
57.17
44.43
22.27
Table 17. Hea ing and cooling demand o he building wi h and wi hou cooling
echnologies du ing TMY

Pàg. 118 Memò ia
HW Pe iods
Hea ing demand [ 𝒌𝑾𝒉 𝒎𝟐
⁄]
Cooling demand [ 𝒌𝑾𝒉 𝒎𝟐
⁄]
BC
NV_BL
Reduc ion
(%)
BC
NV_BL
Reduc ion
(%)
HW_P_L
12.23
2.35
80.80
32.77
22.05
32.69
HW_P_MS
11.44
2.21
80.65
27.23
18.98
30.27
HW_P_MI
13.14
2.59
80.32
24.25
16.09
33.67
HW_MF_MIS
5.37
2.17
59.57
43.79
33.29
23.961
HW_MF_L
6.43
1.73
73.13
40.21
29.82
25.84
HW_LF_LMS
3.06
0.26
91.57
80.28
67.93
15.38
HW_LF_MI
2.16
0.25
88.65
71.10
62.97
11.42
Table 18. Hea ing and cooling demand o he building wi h and wi hou cooling
echnologies du ing HW
As shown in Tables 17 and 18, he cooling demand inc eases o e ime when compa ing
he base case (BC) o TMY_P o ha o TMY_LF. Howe e , he implemen a ion o passi e
cooling echnologies esul s in a no iceable educ ion in cooling demand. Ne e heless, he
e ec i eness o hese echnologies diminishes p og essi ely o e ime, as he educ ions
hey achie e become less signi ican unde u u e clima e condi ions.
Implemen ing he combina ion o na u al en ila ion and blinds in he building allows o
annual sa ings o 67.19% - 80.20% in hea ing and 22.27% - 31.14% in cooling du ing he
long u u e (Table 17).
• The second eason is wha has al eady been men ioned be o e, ha he analysed
case in ol es a building whe e he esiden s ha e low-income le els. The e o e, he
goal is o imp o e hei he mal com o wi hou inc easing hei ene gy bills.
I is impo an o highligh ha wha has been analysed in his sec ion is he building’s
he mal demand, no i s ac ual ene gy consump ion. This dis inc ion is based on wo main
easons:
• Fi s , he ene gy consump ion associa ed wi h ai -condi ioning a dwelling ul ima ely
depends on he beha iou and decisions o i s occupan s. Residen s wi h high
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 119
incomes migh choose no o in es in cooling o hea ing hei spaces, while
con e sely, indi iduals li ing in ene gy po e y may p io i ise spending a signi ican
po ion o hei limi ed income owa ds main aining indoo com o .
• Secondly, he ene gy consump ion o condi ioning sys ems is highly dependen on
he speci ic equipmen ins alled. Fac o s such as he nominal cooling and hea ing
powe , seasonal pe o mance ac o s SEER and SCOP, and he a e age
ope a ional e iciency a y signi ican ly be ween di e en models. Al hough a
p oposal o a low-cos ai -condi ioning sys em could ha e been de eloped o he
s udied building, doing so would ha e been pu o scope o his p ojec . I would
ha e equi ed ex ensi e echnical knowledge ega ding HVAC sys ems, as well as
compliance wi h he equi emen s se by he Spanish Technical Building Code,
CTE.
Pàg. 120 Memò ia
10. Social and gende equali y assessmen
I is impo an o highligh ha his hesis has a social dimension ha has been conside ed
h oughou he en i e p ojec . The aim was o ca y ou a comp ehensi e ene gy s udy
ocused on he mos ulne able social g oups, while e alua ing a ious passi e s a egies
designed o be accessible and implemen able by anyone, hanks o hei low cos .
This sec ion aims o discuss how he implemen a ion o passi e cooling echnologies
impac s he mos ulne able g oups, wi h a pa icula ocus on he neighbou hood o Ciu a
Me idiana, whe e his s udy has been ca ied ou , and i s esiden s. Valuable demog aphic,
social, and economic in o ma ion abou he a ea has been ob ained om he s udy by
Ra e lla Mi a, P. J., Díaz Gómez, C., Co nadó Ba dón, C., & Vima G au, S. [57].
Popula ion analysis:
The popula ion o Ciu a Me idiana is cha ac e ised by a high pe cen age o immig an s o
di e se na ionali ies, signi ican ly exceeding he a e age o he ci y o Ba celona. The
emaining popula ion, composed la gely o elde ly indi iduals and younge gene a ions who
a e e u ning o he neighbou hood due o he housing eme gency and ongoing economic
c isis, also exhibi s a e y low economic s a us.
Despi e he b oade demog aphic end owa ds ageing, Ciu a Me idiana main ains a high
bi h a e, la gely d i en by he immig an popula ion. The a ea is ma ked by high
unemploymen a es and a p edominance o esiden s wi h e y low income le els.
Daily li e in he neighbou hood is signi ican ly a ec ed by issues such as e ic ions and
unemploymen , which ep esen majo social con lic s o i s esiden s. Fu he mo e,
e idence o o e c owded housing condi ions highligh s he se e e esiden ial ulne abili y
aced by many households.
Access o Implemen ed Technologies:
Among he wo passi e cooling echnologies analysed, NV and BL, na u al en ila ion does
no c ea e any o m o disc imina ion based on gende o social g oup, as i equi es no
in es men o ins alla ion. Howe e , he ins alla ion o blinds is no cos ee, so i may pose
an economic ba ie o ulne able households. Ne e heless, once implemen ed, bo h
echnologies ha e minimal o no main enance cos s, making hem accessible in he long
e m o low-income amilies.
Impac on Vulne able G oups:
Passi e cooling echnologies a e pa icula ly bene icial o low-income g oups and o he
mos ulne able membe s o socie y, such as he elde ly and child en, who, acco ding o
he demog aphic da a, ep esen a signi ican pe cen age o he popula ion in Ciu a
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 121
Me idiana. These g oups a e especially sensi i e o ex eme empe a u es, and he
implemen a ion o passi e cooling solu ions can subs an ially imp o e hei li ing condi ions,
enhancing bo h hei heal h and well-being.
Gende Balance in he P ojec Team:
E o s owa ds gende equali y ha e also been conside ed in his p ojec . In his case, he
eam consis s o wo membe s, bo h emale, con ibu ing inclusi e pe spec i es h oughou
he esea ch p ocess. Howe e , i is impo an o no e ha aking a look a he e e ences
ci ed in his hesis e eals ha he majo i y o he au ho s a e male, a bias ha was only
ecognised upon d a ing his sec ion. This highligh s he ongoing need o g ea e gende
di e si y no only in esea ch eams bu also in he b oade academic and scien i ic
li e a u e.
Pàg. 128 Memò ia
o social he i age housing in Medi e anean clima e. Ene gy Repo s, 12, 2328–2345.
h ps://doi.o g/10.1016/j.egy .2024.08.037
[23] Cos a-Campi, M. T., Jo é-Llopis, E., & T ujillo-Bau e, E. (2019). Ene gy po e y in
Spain: an income app oach analysis. In Ene gy Sou ces, Pa B: Economics, Planning and
Policy (Vol. 14, Issues 7–9). h ps://doi.o g/10.1080/15567249.2019.1710624
[24] CYPETHERM LOADS - The mal model. Lib a ies (building elemen s) - CYPE. (n.d.).
Re ie ed Ap il 28, 2025, om h ps://in o.cype.com/en/subjec /cype he m-loads- he mal-
model-lib a ies-building-elemen s/
[25] Djongyang, N., Tchinda, R., & Njomo, D. (2010). The mal com o : A e iew pape .
Renewable and Sus ainable Ene gy Re iews, 14(9), 2626–2640.
h ps://doi.o g/10.1016/J.RSER.2010.07.040
[26] E. C. Thom, “The Discom o Index,” Wea he wise, ol. 12, no. 2, pp. 57–61, Ap . 1959,
doi: 10.1080/00431672.1959.9926960.
[27] EN16798-1:2019. Ene gy Pe o mance o Buildings—Ven ila ion o Buildings—Pa 1:
Indoo En i onmen al Inpu Pa ame e s o Design and Assessmen o Ene gy
Pe o mance o Buildings Add essing Indoo Ai Quali y, The mal En i onmen , Ligh ing
and Acous; Eu opean Commi ee o S anda diza ion: B ussels, Belgium, 2019.
[28] Enescu, D. (2017). A e iew o he mal com o models and indica o s o indoo
en i onmen s. Renewable and Sus ainable Ene gy Re iews, 79, 1353–1379.
h ps://doi.o g/10.1016/J.RSER.2017.05.175
[29] Eu opean Commission - DG JRC DCET h ps://e3p.j c.ec.eu opa.eu/a icles/ ypical-
me eo ological-yea - my. Me eo ological Yea . 9. and C. Typical
[30] Gu ie ez, E. D., Cani ell, J., Hue as, D. B., Bellido, C. R., & Gu ie ez, D. D. (2022).
Ecuado ian Social Housing: Ene ge ic Analysis Based on The mal Com o o Reduce
Ene gy Po e y. Ene gy Po e y Alle ia ion New App oaches and Con ex s, 209–224.
h ps://doi.o g/10.1007/978-3-030-91084-6_9
[31] Gu ie ez, G., & de Angelis, E. (2021). Figh ing ene gy po e y in a ypical Pe u ian
u al house. Jou nal o Physics: Con e ence Se ies, 2042(1), 012158.

Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 129
h ps://doi.o g/10.1088/1742-6596/2042/1/012158
[32] He nandez-C uz, P., U ia e, I., Hidalgo-Be anzos, J. M., An epa a, Í., & Flo es-
Abascal, I. (2023). A no el s a egy o gua an ee a minimum indoo empe a u e in social
housing buildings. Jou nal o Building Enginee ing, 76, 107230.
h ps://doi.o g/10.1016/j.jobe.2023.107230
[33] Hong, T., Malik, J., K elling, A., O’B ien, W., Sun, K., Lambe s, R., & Wei, M. (2023).
Ten ques ions conce ning he mal esilience o buildings and occupan s o clima e
adap a ion. Building and En i onmen , 244, 110806.
h ps://doi.o g/10.1016/J.BUILDENV.2023.110806
[34] h ps://en.wikipedia.o g/wiki/We -bulb_ empe a u e
[35]h ps://www.codigo ecnico.o g/pd /Documen os/HE/DA_DB-HE-
1_Calculo_de_pa ame os_ca ac e is icos_de_la_en ol en e.pd
[36] Idesca . Índice socioeconómico e i o ial. Indicado es socioeconómicos. Valo es. Po
ba ios de Ba celona. Ba celona. (n.d.). Re ie ed Ap il 28, 2025, om
h ps://www.idesca .ca /pub/?id=is &n=14075&geo=mun:080193&lang=es
[37] INFORME SOCIO-RESIDENCIAL DEL BARRIO DE CIUTAT MERIDIANA EN
BARCELONA. (2010).
[38] Io dache, V., Teodosiu, C., Teodosiu, R., & Ca alina, T. (2016). Pe meabili y
Measu emen s o a Passi e House du ing Two Cons uc ion S ages. Ene gy P ocedia, 85,
279–287. h ps://doi.o g/10.1016/j.egyp o.2015.12.253
[39] L. Bo ghe o, E. Clè ies, T. Péan, J. O iz, and J. Salom, “Compa ing cooling s a egies
o assess he mal com o esilience o esiden ial buildings in Ba celona o p esen and
u u e hea wa es,” Build En i on, p. 110043, Ma . 2023, doi:
10.1016/j.builden .2023.110043.
[40] Li, K., Lloyd, B., Liang, X. J., & Wei, Y. M. (2014). Ene gy poo o uel poo : Wha a e
he di e ences? Ene gy Policy, 68, 476–481.
h ps://doi.o g/10.1016/J.ENPOL.2013.11.012
[41] M. Hamdy, S. Ca lucci, P. J. Hoes, and J. L. M. Hensen, “The impac o clima e change
on he o e hea ing isk in dwellings—A Du ch case s udy,” Build En i on, ol. 122, pp. 307–
323, Sep. 2017, doi: 10.1016/j.builden .2017.06.031.
[42] M. y A. U. Minis e io de T anspo es, “Guía de aplicación DB HE 2019,” 2019. [39]
Pàg. 130 Memò ia
[43] M.Russinyol, “ Es udi de l’impac e del can i climà ic jun amb l’ús de ecnologies de
e ige ació i ehabili acions esilien s en les edi icacions de Ca alunya” Escola Tècnica
Supe io d’Enginye ia de Ba celona, Ba celona, 2024
[44] Macha d A, Ina d C, Alessand ini JM, Pelé C, Ribé on J. A Me hodology o Assembling
Fu u eWea he Files including Hea wa es o Building The mal Simula ions om he
Eu opean Coo dina ed Regional Downscaling Expe imen (EURO-CORDEX) Clima e
Da a. Ene gies (Basel). 2020 Jul 1;13(13).
[45] Ma acchini, G., di Giuseppe, E., & D’O azio, M. (2023). Ene gy Po e y and
Hea wa es. Expe imen al In es iga ion on Low-Income Households’ Ene gy Beha io .
Sma Inno a ion, Sys ems and Technologies, 336, 271–280. h ps://doi.o g/10.1007/978-
981-19-8769-4_26
[46] Masana López, A. (n.d.). S udy o ene gy sa ings and he mal pe o mance o esilien
cooling echnologies in exis ing buildings in con inen al Medi e anean clima e REPORT
Au ho .
[47] Membe S a e Repo Spain. (n.d.). Re ie ed Ap il 8, 2025, om
www.ene gypo e y.eu
[48] Mo e a, M. A. (n.d.). S udy o he mal pe o mance and ene gy sa ings o esilien
cooling echnologies in exis en buildings in con inen al Medi e anean clima e REPORT
Au o /a.
[49] N. R. M. Sakiyama, L. Mazza e o, J. C. Ca lo, T. Beja , and H. Ga ech , “Na u al
en ila ion po en ial om wea he analyses and building simula ion,” Ene gy Build, ol. 231,
Jan. 2021, doi: 10.1016/j.enbuild.2020.110596.
[50] Na ional Oceanic and A mosphe ic Adminis a ion, “Hea Index”.
[51] O.C espo, “ Es udio del impac o de ecnologías de e ige ación esilien es en
edi icaciones exis en es en zonas de al a mon aña,” Escola Tècnica Supe io d’Enginye ia
de Ba celona, Ba celona, 2024
[52] Obse a o y | Ene gy Po e y Ad iso y Hub. (n.d.). Re ie ed Ap il 28, 2025, om
h ps://ene gy-po e y.ec.eu opa.eu/obse a o y
[53] Pas o , F., & Khodaya , S. (2023). Ma ine hea wa es: Cha ac e izing a majo clima e
impac in he Medi e anean. Science o The To al En i onmen , 861, 160621.
h ps://doi.o g/10.1016/J.SCITOTENV.2022.160621
[54] Pe ei a-Ruchansky, L., & Pé ez-Fa gallo, A. (2023). Impac o Passi e Design
Measu es on he The mal Com o o Social Housing in he Con ex o Clima e Changein
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 131
Mon e ideo, U uguay. In G een Ene gy and Technology (pp. 387–400). Sp inge Science
and Business Media Deu schland GmbH. h ps://doi.o g/10.1007/978-3-031-24208-3_27
[55] P ojec - Cool o ise. (n.d.). Re ie ed Ap il 28, 2025, om h ps://cool o ise.eu/abou -
he-p ojec /
[56] R. S ull, “We -bulb empe a u e om ela i e humidi y and ai empe a u e,” J Appl
Me eo ol Clima ol, ol. 50, no. 11, pp. 2267–2269, No . 2011, doi: 10.1175/JAMC D-11-
0143.1.
[57] Ra e lla Mi a, P. J., Díaz Gómez, C., Co nadó Ba dón, C., & Vima G au, S. (2019). La
millo a de les condicions d’habi abili a en els g ans conjun s esidencials de l’À ea
Me opoli ana de Ba celona. In La millo a de les condicions d’habi abili a en els g ans
conjun s esidencials de l’À ea Me opoli ana de Ba celona. Inicia i a Digi al Poli ècnica.
O icina de Publicacions Acadèmiques Digi als de la UPC. h ps://doi.o g/10.5821/ebook-
9788498807943
[58] Realini, A., Maggio e, S., Bo ga ello, M., & Zenga ini, N. (2022). Ene gy po e y and
heal h: he e ec o poo housing on people’s wellbeing. Eceee Summe S udy
P oceedings, 521–531.
[59] Ro h usz LP. The Hea Index “Equa ion” (o , Mo e Than You E e Wan ed o Know
Abou Hea Index). 1990.
[60] S. A ia, R. Rahi , V. Co ado, and P. Di To ino, “F amewo k o e alua e he esilience
o di e en cooling echnologies Ligh ing and The mal Pe o mance me ics o Tubula
dayligh ing de ices View p ojec [Su Chau e] O e hea ing Indica o and Calcula ion
Me hod o Walloon Buildings View p ojec ,” 2021, doi: 10.13140/RG.2.2.33998.59208.
[61] Sal ans Baucells, J. (n.d.). Sys ema ic analysis o esilience in Medi e anean exis ing
buildings Sys ema ic analysis o esilience in Medi e anean exis ing buildings REPORT
Au ho .
[62] Sal a i A, Macha d A, Pou abdollah oo kaboni M, Gau A. In oduc ion: Pu pose o he
Wea he da a Wo kshop in he con ex o he Annex 80.
[63] Sánchez-Ga cía, D.; Bien enido-Hue as, D.; T is ancho-Ca ajal, M.; Rubio-Bellido,
C. Adap i e Com o Con ol Implemen ed Model (ACCIM) o Ene gy Consump ion
P edic ions in Dwellings unde Cu en and Fu u e Clima e Condi ions: A Case S udy
Loca ed in Spain. Ene gies 2019, 12, 1498. [C ossRe ]
Pàg. 132 Memò ia
[64] Sánchez-Gue a a Sánchez, C., Sanz Fe nández, A., Núñez Pei ó, M., & Gómez
Muñoz, G. (2020). Ene gy po e y in Mad id: Da a exploi a ion a he ci y and dis ic le el.
Ene gy Policy, 144. h ps://doi.o g/10.1016/j.enpol.2020.111653
[65] Siksnely e-Bu kiene, I., S eimikiene, D., Leka icius, V., & Balezen is, T. (2021). Ene gy
po e y indica o s: A sys ema ic li e a u e e iew and comp ehensi e analysis o in eg i y.
Sus ainable Ci ies and Socie y, 67, 102756. h ps://doi.o g/10.1016/J.SCS.2021.102756
[66] S ama opoulos, E., Fo ouli, A., S oian, D., Kouloukakis, P., Sa mas, E., & Ma inakis,
V. (2024). An adap i e amewo k o assessing clima e esilience in buildings. Building and
En i onmen , 264, 111869. h ps://doi.o g/10.1016/J.BUILDENV.2024.111869
[67] S asi, R., Ruggie o, F., & Be a di, U. (113836). Na u al en ila ion e ec i eness in low-
income housing o challenge ene gy po e y. Volume 304, 304.
h ps://doi.o g/10.1016/j.enbuild.2023.113836
[68] Sus ainable Home Design | Na u al Ven ila ion. (n.d.). Re ie ed Ap il 22, 2025, om
h ps://www. heups udio.com/sus ainablehomedesign/na u al en ila ion.h ml
[69] Sy, S. A., & Mokaddem, L. (2022). Ene gy po e y in de eloping coun ies: A e iew o
he concep and i s measu emen s. In Ene gy Resea ch and Social Science (Vol. 89).
h ps://doi.o g/10.1016/j.e ss.2022.102562
[70] Ton odona i, “S udy o ene gy sa ings and en i onmen al and economic impac o
esilien cooling echnologies in exis ing buildings,” Escola Tècnica Supe io d’Enginye ia
de Ba celona, Ba celona, 2023.
[71] UNE No malización Española, “UNE-EN 16798-1:2020.” Accessed: Dec. 16, 2023.
[Online]. A ailable: no ma/no ma?c=N0063261 h ps://www.une.o g/encuen a- u-
no ma/busca- u
[72] UNE No malización Española, “UNE-EN ISO 7730:2006”, Accessed: Dec. 16, 2023.
[Online]. A ailable: no ma/no ma?c=N0037517 h ps://www.une.o g/encuen a- u-
no ma/busca- u
[73] Uni e sidad Poli écnica de Mad id. (n.d.). Re ie ed Ap il 28, 2025, om
h ps://www.upm.es/In es igacion/?id=CON17988&p e m =a iculo& m =de ail
[74] V. C. C. Lee and K. S. Yam, “In oduc ion o opens udio® o wo k in eg a ed lea ning:
Case s udy on building ene gy modelling,” in Communica ions in Compu e 121 S udy o
ene gy sa ings and he mal pe o mance o esilien cooling echnologies in exis ing
buildings in con inen al Medi e anean clima e. and In o ma ion Science, Sp inge Ve lag,
Assessmen o clima e esilience in ulne able buildings in he ci y o Ba celona Pág. 133
2017, pp. 349–358. doi: 10.1007/978 981-10-6502-6_31.
[75] Vu o, G., San ama ia, V., Chia an oni, C., & Fio i o, F. (2022). Clima e Change Impac
on Ene gy Po e y and Ene gy E iciency in he Public Housing Building S ock o Ba i, I aly.
Clima e, 10(4), 55. h ps://doi.o g/10.3390/cli1004005
[76] WCRP. Wo ld Clima e Resea ch P og amme Coo dina ed Regional Clima e
Downscaling Expe imen . h ps://co dex.o g/abou /wha -is- egional-downscaling/. Abou
CORDEX.
[77] wea he .go , “Wha is he hea index?” Accessed: Jan. 05, 2024. [Online]. A ailable:
h ps://www.wea he .go /ama/hea index
[78] whea he .go ,“Wha is he hea index?” Accessed: Jan. 05, 2024. [Online]. A ailable:
h ps://www.wea he .go /ama/hea index
[79] www.comillas.edu/ca ed a-de-ene gia-y-pob eza www.comillas.edu/ca ed a-de-
ene gia-y-pob eza Página 2 de 34. (n.d.). www.comillas.edu/ca ed a-de-ene gia-y-pob eza
[80] Y. Eps ein and D. S. Mo an, “The mal Com o and he Hea S ess Indices,” 2006.
[81] Zhao, H., Ji, W., Deng, S., Wang, Z., & Liu, S. (2024). A e iew o dynamic he mal
com o in luenced by en i onmen al pa ame e s and human ac o s. Ene gy and Buildings,
318, 114467. h ps://doi.o g/10.1016/J.ENBUILD.2024.114467