Improving the Earthquake Resilience of Primary Schools in the Border Regions of Neighbouring Countries

Abstract

This work summarises the strategy adopted in the European research project PERSISTAH. It aims to increase the resilience of the population, focusing on the existing primary schools in the Algarve (Portugal) and Huelva (Spain) regions. Software was developed to assess the seismic safety of these schools, considering different earthquake scenarios. Seismic retrofitting measures were studied and numerically tested. Some of them were also implemented in the retrofitting activities of two case study schools (one in each country). It was found that the adopted ground motion prediction equations (GMPEs) considerably affect the results obtained with the software, especially for offshore earthquake scenarios. Furthermore, the results show that the masonry buildings would be the most damaged school typologies for all the scenarios considered. Additionally, a set of guidelines was created to support the school community and the technicians related to the construction industry. The goal of these documents is to increase the seismic resilience of the population. Different activities were carried out to train schoolteachers in seismic safety based on the guidelines produced, obtaining positive feedback from them.

Full text

Citation: Estêvão, J.M.C.;
Morales-Esteban, A.; Sá, L.F.; Ferreira,
M.A.; Tomás, B.; Esteves, C.; Barreto,
V.; Carreira, A.; Braga, A.;
Requena-Garcia-Cruz, M.-V.; et al.
Improving the Earthquake Resilience
of Primary Schools in the Border
Regions of Neighbouring Countries.
Sustainability 2022,14, 15976.
https://doi.org/10.3390/
su142315976
Academic Editors: Vittorio Rosato,
Maurizio Pollino, Sonia Giovinazzi
and Paolo Clemente
Received: 31 October 2022
Accepted: 23 November 2022
Published: 30 November 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
sustainability
Article
Improving the Earthquake Resilience of Primary Schools in the
Border Regions of Neighbouring Countries
João M. C. Estêvão1, 2, * , Antonio Morales-Esteban 3, Luis F. Sá4, Mónica A. Ferreira 5, Bruno Tomás1,
Carlos Esteves 1, Vítor Barreto 1, Ana Carreira 1, Alfredo Braga 1, Maria-Victoria Requena-Garcia-Cruz 3,
Emilio Romero-Sanchez 3, Jaime de-Miguel-Rodriguez 3, Maria-Luisa Segovia-Verjel 3, Beatriz Zapico Blanco 3
and Carlos Sousa Oliveira 5
1Department of Civil Engineering, ISE, University of Algarve, 8005-217 Faro, Portugal
2
CIMA—Centre for Marine and Environmental Research, UAlg, Campus de Gambelas, 8005-139 Faro, Portugal
3Department of Building Structures and Geotechnical Engineering, University of Seville, 41004 Seville, Spain
4Autoridade Nacional de Emergência e Proteção Civil, 2794-112 Carnaxide, Portugal
5CERIS—Instituto Superior Técnico, 1049-001 Lisboa, Portugal
*Correspondence: jestevao@ualg.pt; Tel.: +351-289-800-154
Abstract:
This work summarises the strategy adopted in the European research project PERSISTAH.
It aims to increase the resilience of the population, focusing on the existing primary schools in the
Algarve (Portugal) and Huelva (Spain) regions. Software was developed to assess the seismic safety
of these schools, considering different earthquake scenarios. Seismic retrofitting measures were
studied and numerically tested. Some of them were also implemented in the retrofitting activities of
two case study schools (one in each country). It was found that the adopted ground motion prediction
equations (GMPEs) considerably affect the results obtained with the software, especially for offshore
earthquake scenarios. Furthermore, the results show that the masonry buildings would be the most
damaged school typologies for all the scenarios considered. Additionally, a set of guidelines was
created to support the school community and the technicians related to the construction industry.
The goal of these documents is to increase the seismic resilience of the population. Different activities
were carried out to train schoolteachers in seismic safety based on the guidelines produced, obtaining
positive feedback from them.
Keywords:
earthquake resilience; school buildings; earthquake scenarios; pushover analysis;
risk education; PERSISTAH
1. Introduction
One of the 17 Sustainable Development Goals (SDGs) that were adopted by the Unit-
ed Nations (UN) [
1
] includes resilience (goal 11: Make cities and human settlements
inclusive, safe, resilient, and sustainable). In this context and in earthquake-prone regions,
improving the earthquake resilience of communities is a very important issue. There are
many definitions of resilience, with different types and dimensions [
2
,
3
]. Despite that, it
seems evident that post-traumatic disturbance after an earthquake considerably depends
on the resilience of the population [
4
]. This might be a relevant problem in schools due to
the possible presence of very young children. This is even more problematic in primary
school buildings. Therefore, it is crucial to improve the earthquake resilience of this type of
construction to reduce the impact of catastrophic situations in the education system. In fact,
school buildings have presented important seismic damage all over the world [
5
–
9
]. This
can also be related to the relative position of school buildings to the earthquake rupture [
10
].
The reduction in the seismic risk is the result of a combination of actions, processes
and attitudes aiming to improve resilience. These can be divided into three main groups
of activities [
11
]: prevention (usually by building schools in proper locations and with an
adequate seismic resistance), mitigation (by retrofitting the most vulnerable buildings and
Sustainability 2022,14, 15976. https://doi.org/10.3390/su142315976 https://www.mdpi.com/journal/sustainability

Sustainability 2022,14, 15976 2 of 24
communicating this need to teachers, students and the whole community where the school
is placed, for example), and preparation (by creating emergency plans, training in the earth-
quake context, producing guidelines for teachers and learning materials for students about
this issue, and alerting the community to the seismic risk). In this context, civil protection
agencies usually promote the development of tools for risk and crisis management, aiming
to increase the protection of people and property against earthquake disasters.
Regarding the existing school buildings, prevention is not an option: it is not possible
to change their location. Additionally, they might not have enough seismic resistance due
to their construction date. In fact, they might not comply with the requirements of new
seismic codes. To solve this problem, the only possible solution is to carry out activities
related to mitigation and preparation.
The existing methods for the seismic vulnerability assessment of buildings can be
divided into three major groups [
12
]: the empirical methods, usually based on statistical
mean data obtained in post-earthquake scenarios and in expert knowledge; the analyti-
cal/mechanical methods, which are normally based on structural analyses to assess seismic
safety according to different limit states (LS); and the hybrid methods, which gather charac-
teristics of the other two methods.
The empirical methods are more suitable for large-scale seismic risk studies. The
analytical/mechanical methods seem to be more adequate to study individual buildings.
This is due to the possible differences in the results of each type of approach, as shown by
recent studies [13].
The seismic vulnerability of the structural elements of school buildings is of great
importance. In fact, it can lead to the collapse of the building. However, it is also important
to understand the seismic behaviour of non-structural elements. Recent tests, carried out
on shaking tables, highlighted the effects of earthquakes on non-structural elements that
usually exist in buildings [
14
]. This might be especially important in buildings presenting
low seismic vulnerability, or in general when buildings are subject to low levels of vibration.
This is especially important when there is the possibility of a high concentration of people,
as in school buildings.
Past earthquakes seem to evidence the key role that schools have with regard to society
in the event of an earthquake and at different levels [
15
]. Besides their importance regarding
seismic performance, it is also necessary to ensure that teachers are trained. They can better
transmit their knowledge about earthquakes to the students but also act accordingly in
case of a seismic emergency [
16
,
17
]. The importance of schools in the seismic resilience
of a modern society is the goal of many studies. These adopt a wide range of strategies
based on the requirements of each country where the study is carried out. In addition,
they bear in mind the number of school buildings that are studied. Thus, it is necessary to
understand the real structural behaviour of each school building, either through laboratory
studies [18] or complemented through numerical studies.
Recent works using more rigorous analytical methods have been normally carried out
only for individual buildings, such as schools or hospitals. In this context, it is usual to adopt
nonlinear static analyses [
19
–
23
] or nonlinear dynamic analyses [
24
–
29
]. The latter are more
rigorous, but they require more computational effort. These aspects should be considered
in the case of large-scale studies. However, the use of these methods is also the best way to
understand the influence of the level of conservation on the seismic safety of schools [
30
].
They are also useful to evaluate the effectiveness of seismic retrofitting measures [
31
,
32
].
Simplified empirical methods are widely applied as well [
33
]. Contrariwise, these are
essentially supported by visual inspections and expert knowledge and can be easily applied
to a large number of schools [34,35].
For large-scale studies on the seismic safety of schools, it is common to use algorithms
from other scientific areas, using empirical information to maximise the accuracy of the
results. Such is the case of machine learning (expert systems, genetic algorithms, and
neural networks, for example) [
36
–
38
], as well as the development of specific computer
tools [39,40].

Sustainability 2022,14, 15976 3 of 24
It should be noted that earthquake effects cross borders between countries. Therefore,
studies should not be limited by these national borders, such as is the case of the European
research project PERSISTAH (Projetos de Escolas Resilientes aos SISmos no Território do Algarve
e de Huelva, in Portuguese, or Projects of Earthquake-Resilient Schools of the Algarve and Huelva,
in English). The area under study is the Algarve (Portugal) and Huelva (Spain) provinces,
which are next to each other near the Portugal–Spain border. The project is focused on
the agreements of Hyogo [
41
] and Sendai [
42
] on the cooperation to reduce countries’
seismic risk.
The research steps of the project are outlined in Figure 1. First, a survey of the existing
primary schools in the regions under study was carried out to create a database. Then,
nonlinear structural analyses of a set of school buildings of different construction dates
and structural systems were carried out. The outputs of these analyses were added to
a software that was developed in the context of the PERSISTAH project. This allows us
to perform the seismic assessment of individual school buildings and create ranked lists
based on their individual safety. These lists can be instantly exported to a KML file and
displayed in Google Earth, or in Google Maps, with a colour scale. Additionally, this
allows us to place the maps with the results on a website with an intuitive and interactive
interface. This information is especially useful for civil protection authorities. The results
are helpful to support mitigation and preparation activities (from enhancing emergency
planning to facilitating technical training and exercises, in the civil protection context).
Furthermore, it enables us to improve the risk communication to the population. After
identifying the most vulnerable school typologies, two case study schools were selected
for their seismic retrofitting (one located in the Algarve and the other in Huelva). Training
actions were also carried out for teachers and for the technical community of the two
regions under study. Several guides were produced to support teachers, students, and civil
construction technicians.
Sustainability 2022, 14, x FOR PEER REVIEW 3 of 26
Contrariwise, these are essentially supported by visual inspections and expert knowledge
and can be easily applied to a large number of schools [34,35].
For large-scale studies on the seismic safety of schools, it is common to use algorithms
from other scientific areas, using empirical information to maximise the accuracy of the
results. Such is the case of machine learning (expert systems, genetic algorithms, and
neural networks, for example) [36–38], as well as the development of specific computer
tools [39,40].
It should be noted that earthquake effects cross borders between countries. Therefore,
studies should not be limited by these national borders, such as is the case of the European
research project PERSISTAH (Projetos de Escolas Resilientes aos SISmos no Território do
Algarve e de Huelva, in Portuguese, or Projects of Earthquake-Resilient Schools of the Algarve
and Huelva, in English). The area under study is the Algarve (Portugal) and Huelva (Spain)
provinces, which are next to each other near the Portugal–Spain border. The project is
focused on the agreements of Hyogo [41] and Sendai [42] on the cooperation to reduce
countries' seismic risk.
The research steps of the project are outlined in Figure 1. First, a survey of the existing
primary schools in the regions under study was carried out to create a database. Then,
nonlinear structural analyses of a set of school buildings of different construction dates
and structural systems were carried out. The outputs of these analyses were added to a
software that was developed in the context of the PERSISTAH project. This allows us to
perform the seismic assessment of individual school buildings and create ranked lists
based on their individual safety. These lists can be instantly exported to a KML file and
displayed in Google Earth, or in Google Maps, with a colour scale. Additionally, this
allows us to place the maps with the results on a website with an intuitive and interactive
interface. This information is especially useful for civil protection authorities. The results
are helpful to support mitigation and preparation activities (from enhancing emergency
planning to facilitating technical training and exercises, in the civil protection context).
Furthermore, it enables us to improve the risk communication to the population. After
identifying the most vulnerable school typologies, two case study schools were selected
for their seismic retrofitting (one located in the Algarve and the other in Huelva). Training
actions were also carried out for teachers and for the technical community of the two
regions under study. Several guides were produced to support teachers, students, and
civil construction technicians.
Figure 1. Flowchart of the PERSISTAH project approach and some inputs–outputs.
Figure 1. Flowchart of the PERSISTAH project approach and some inputs–outputs.
As mentioned, owing to the difficulties of large-scale seismic risk studies of schools, it
is usual to simplify the seismic vulnerability assessment procedures. However, this entails
a substantial increase in uncertainty regarding the reliability of the results, which is often
unknown. The innovative feature of the PERSISTAH project is related to the use of the
most advanced structural analysis methods that are established in the Eurocodes for the
large-scale assessment of school buildings. To do so, a computer tool, which allows us to
improve the knowledge about the main factors that may influence the seismic behaviour of

Sustainability 2022,14, 15976 4 of 24
school constructions, was developed. This information was also included in the guides that
were created to help civil construction professionals. More than just thinking about creating
a finished, watertight product, which often characterises this type of research project, it
was sought to create a methodology and a set of tools that can be continuously updated,
namely for civil protection purposes.
2. Developing a Computational Strategy for the Seismic Assessment
Software was developed in the framework of the PERSISTAH project due to the high
number of primary schools in the Algarve–Huelva regions. The main goal of this software
is to identify school buildings that do not comply with the safety criteria established in the
seismic codes that are mandatory in each country. The software was developed in Object
Pascal (Delphi) and consists of several modules (Figure 2). These modules are associated
with a set of independent, yet fully interconnectable, computational objects [
43
] that re-
sulted from the dismemberment of previously developed software, such as SIMULSIS [
44
].
This feature gave the new software unique characteristics since it inherited the attributes of
the original computer programmes in a symbiotic way, such as the user interfaces.
Sustainability 2022, 14, x FOR PEER REVIEW 5 of 26
Figure 2. Global organisation of the PERSISTAH project software.
2.1. Schools Database
The data about schools were gathered and included in a database. Similar infor-
mation was obtained for schools of each country and used in the adopted seismic safety
assessment procedure. Instead of using a generic database software, a specific database
was developed adopting some innovative strategies. Such is the case of the creation of a
visual system that allows the user to easily have access to information about schools. The
database allows us to save that information and export it to external software since it is
georeferenced. It enables the creation of a KML file to use in Google Earth or MS Excel
files directly through the clipboard.
In total, 281 primary schools in the Algarve–Huelva region were added to the data-
base. Each school campus might be composed of several buildings or structurally inde-
pendent modules. In some cases, these buildings were built at different times, and they
might present different structural systems. Therefore, evaluating their seismic safety with
high accuracy is difficult to accomplish.
2.1.1. Primary Schools in the Algarve Region (Portugal)
Many of the existing school buildings in the Algarve were built with standardised
designs. This facilitated the study of their seismic safety given the high number of existing
Figure 2. Global organisation of the PERSISTAH project software.

Sustainability 2022,14, 15976 5 of 24
2.1. Schools Database
The data about schools were gathered and included in a database. Similar information
was obtained for schools of each country and used in the adopted seismic safety assessment
procedure. Instead of using a generic database software, a specific database was developed
adopting some innovative strategies. Such is the case of the creation of a visual system that
allows the user to easily have access to information about schools. The database allows
us to save that information and export it to external software since it is georeferenced. It
enables the creation of a KML file to use in Google Earth or MS Excel files directly through
the clipboard.
In total, 281 primary schools in the Algarve–Huelva region were added to the database.
Each school campus might be composed of several buildings or structurally independent
modules. In some cases, these buildings were built at different times, and they might
present different structural systems. Therefore, evaluating their seismic safety with high
accuracy is difficult to accomplish.
2.1.1. Primary Schools in the Algarve Region (Portugal)
Many of the existing school buildings in the Algarve were built with standardised
designs. This facilitated the study of their seismic safety given the high number of existing
schools. However, it was not possible to analyse all the buildings of the 142 schools that
were included in the database because the structural configurations of the buildings were
rather different. Thus, the study focused on studying the buildings that could be more
vulnerable based on their characteristics: (i) traditional masonry buildings; (ii) reinforced
concrete (RC) structures constructed prior to the application of the seismic codes in Portugal;
(iii) existing buildings with much lower seismic requirement levels than those currently
established by Part 1 of Eurocode 8 (EC8-1) [
45
] and the respective National Annex (NP EN
1998-1:2010 [46]).
Some of the most vulnerable constructions are the oldest masonry school buildings. It
should be noted that these buildings were constructed according to a set of standardised
designs developed for the Algarve by several architects before the first Portuguese seismic
code. They are part of the so-called “Plano dos Centenários”. Examples of these designs are
those created by Raul Lino in the 1930s, Alberto Braga de Sousa in the 1940s or Fernando
Peres in the 1950s. In this case, it was possible to gather information of the architectural
designs of most of those schools. Additionally, documents related to the construction works
were also available. Therefore, it was possible to carry out the structural analysis of many
buildings belonging to these typologies. Many of these buildings are still functioning as
schools; others are occupied by Administrations [47].
The following standardised designs date from the 1970s. In this case, this group of
buildings has RC structures. The architecture designs of the so called “P3” schools were
created at this time. This is an RC typology commonly found in the Algarve. Unfortunately,
no structural blueprints were found. Fortunately, these buildings present columns and
beams with exposed concrete. It was possible to identify the location of the reinforcements,
as well as the mechanical properties of the materials, based on the results of in situ non-
destructive testing procedures. This knowledge allowed the determination of capacity
curves [48].
In the case of most modern schools, each building has its own design, not following
standardised ones.
2.1.2. Primary Schools in the Huelva Region (Spain)
In Huelva, a total of 139 primary schools (269 different buildings) were identified. First,
they were grouped according to their structural system and to their date of construction.
Later, they were classified according to their geometry and their volumetry. It was found
that 82% of the buildings were constructed with RC frames, 13% with unreinforced masonry
walls and 4% with steel frames. It was not possible to identify the structural system of only
1% of the buildings.

Sustainability 2022,14, 15976 6 of 24
Regarding the construction date, 48% of the buildings were built during the 1970s
and 1980s; therefore, they were built before the application of seismic codes in Spain. Most
of the masonry buildings were built before 1970, while the RC buildings were mainly
constructed after that period (1970s–1980s). Regarding the geometry, they were classified
into six different groups according to the aerial views and on-site visits: compact, linear,
prism, intersection, juxtaposition, and sportive. It was found that 36% and 34% of them are
compact or linear, respectively. The compact buildings are characterised by a square shape,
while the linear structures are rectangular. Further information on the classification of the
buildings can be obtained in [49].
2.2. Seismic Action
This is a module of the developed software in which it is possible to select the seismic
action to be used in the seismic safety assessment of each school building. Different
types of seismic actions can be selected: (i) the code-based seismic action, mandatory
in each municipality where the school is located, to verify the compliance of the legal
requirements; (ii) the seismic action resulting from a given earthquake scenario, to support
civil protection activities.
2.2.1. Code-Based Seismic Action
In this case, the seismic action is represented by the EC8-1 response spectrum. A
computational object was created with different subclasses, one for each country. The
same computer routines were always used, regardless of the country, the region, and
the municipality. Therefore, the results were more easily obtained. For the Algarve, the
response spectra established in the mandatory NP EN 1998-1:2010 [
46
] were implemented.
For Huelva, the current Spanish seismic code, the NCSE-02 [50], was implemented.
By using this software, it was easier to compare the differences between the maximum
values of the design ground acceleration for schools in the border regions of the Algarve
and Huelva. The peak acceleration a
g
of the EC8-1 (Equation (1)), which depends on the
reference peak acceleration (agR) and on the importance factor (γI), is equal to:
ag=agR ·γI(1)
It is evident that the seismic hazard does not bear in mind borders between countries.
Therefore, the seismic codes of each country should not present very different values. In fact,
this is the idea on which the European Seismic Hazard Model (ESHM) was based, which
supported the creation of the ESHM13 [
51
] and the new ESHM20 [
52
] models. Contrary to
this idea of harmonisation, it was possible to observe very significant differences on the
border between Portugal and Spain (Figure 3). This is due to two reasons: (i) the reference
peak ground accelerations (agR) are higher in the Portuguese seismic code for the Algarve
region; (ii) the importance factor for schools is higher than one in the NP EN 1998-1:2010
for the Algarve region, while this value is equal to one in the NCSE-02 for the Huelva
region. From a practical point of view, the return period (T
R
) of the seismic action that
must be used to check the safety of schools in the Algarve is 821 years, in accordance with
the Portuguese National Annex of Part 5 of Eurocode 8 (EC8-5) [
53
], while in the region of
Huelva, the Spanish NCSE-02 adopts TR= 475 years.
2.2.2. Earthquake Scenarios
This functionality implemented in the developed software enables the definition of
earthquake scenarios. This is particularly useful for the civil protection authorities since
it allows us to assess the possible impact of this natural phenomenon on the evaluated
schools. For each earthquake occurrence scenario, it is necessary to define the magnitude of
the event, the characteristics of the rupture (which can be a point source, a line, or a plane),
the type of seismic fault, and the geographic location of the earthquake rupture.
It seems evident that it is not scientifically correct to idealise earthquakes of any
magnitude and location. This may lead to effects on school buildings whose probability of

Sustainability 2022,14, 15976 7 of 24
occurrence is quite low. In this work, to illustrate the potential of the software developed,
scenarios whose magnitudes are stipulated in official documents were chosen [
53
]. Their
locations are selected according to the seismic faults identified in international scientific
publications, or where earthquakes have occurred in the past.
Sustainability 2022, 14, x FOR PEER REVIEW 8 of 26
Figure 3. Values of ag that are established in national codes for the primary school buildings placed
in the regions of the Algarve and Huelva (range between a maximum 3.90 m/s2, in the Algarve
region, and a minimum 0.61 m/s2 in the Huelva region). At the border, the discontinuity is from 2
to 1.
It seems evident that it is not scientifically correct to idealise earthquakes of any mag-
nitude and location. This may lead to effects on school buildings whose probability of
occurrence is quite low. In this work, to illustrate the potential of the software developed,
scenarios whose magnitudes are stipulated in official documents were chosen [53]. Their
locations are selected according to the seismic faults identified in international scientific
publications, or where earthquakes have occurred in the past.
It is not usual for seismic codes to establish the magnitude of the earthquakes for a
given seismic action because they express seismic actions throughout a uniform probabil-
ity response spectrum. Therefore, they do not correspond to an isolated event and loca-
tion, but to a set of seismic events related to a certain probability of exceedance. Never-
theless, hazard disaggregation analyses [54] can enable the establishment of scenarios for
the occurrence of earthquakes with return periods consistent with those established in a
seismic code. To do so, two types of events were selected according to the magnitudes
indicated in the Portuguese National Annex of the EC8-5 [53] for liquefaction studies in
the Algarve region: an offshore far-field earthquake with magnitude M = 7.7, and a near-
field earthquake with magnitude M = 5.2. Both correspond to a return period of 821 years.
For a return period of 475 years, the magnitudes for these two scenarios are M=7.4 and M
= 5.1, respectively. Nevertheless, the possible locations of these seismic events are not in-
dicated in the EC8-5. The seismic hazard disaggregation analysis [54] showed that the São
Vicente Canyon area is the one with the highest probability of originating the seismic ac-
tion established in the EC8-1 for the Algarve region. The zone between the Guadalquivir
Bank and the Guadalquivir Fault [55] is another area with high seismic activity. It corre-
sponds to a cluster [56] where there seems to be seismic faults whose total dimension can
originate an offshore earthquake of magnitude M = 7.7.
Figure 3.
Values of a
g
that are established in national codes for the primary school buildings placed in
the regions of the Algarve and Huelva (range between a maximum 3.90 m/s
2
, in the Algarve region,
and a minimum 0.61 m/s2in the Huelva region). At the border, the discontinuity is from 2 to 1.
It is not usual for seismic codes to establish the magnitude of the earthquakes for a
given seismic action because they express seismic actions throughout a uniform probability
response spectrum. Therefore, they do not correspond to an isolated event and location, but
to a set of seismic events related to a certain probability of exceedance. Nevertheless, hazard
disaggregation analyses [
54
] can enable the establishment of scenarios for the occurrence
of earthquakes with return periods consistent with those established in a seismic code.
To do so, two types of events were selected according to the magnitudes indicated in the
Portuguese National Annex of the EC8-5 [
53
] for liquefaction studies in the Algarve region:
an offshore far-field earthquake with magnitude M = 7.7, and a near-field earthquake with
magnitude M= 5.2. Both correspond to a return period of 821 years. For a return period
of 475 years, the magnitudes for these two scenarios are M= 7.4 and M= 5.1, respectively.
Nevertheless, the possible locations of these seismic events are not indicated in the
EC8-5.
The seismic hazard disaggregation analysis [
54
] showed that the São Vicente Canyon
area is the one with the highest probability of originating the seismic action established
in the
EC8-1
for the Algarve region. The zone between the Guadalquivir Bank and the
Guadalquivir Fault [
55
] is another area with high seismic activity. It corresponds to a
cluster [
56
] where there seems to be seismic faults whose total dimension can originate an
offshore earthquake of magnitude M = 7.7.
According to the Spanish IGN [
57
] (Instituto Geográfico Nacional) earthquake catalogue,
an earthquake of a magnitude greater than 4.5 (happening in this offshore area after 1961)
occurred on 3 January, 2005, with an epicentre located at latitude 36.6161
◦
and longitude
−
7.5947
◦
. This corresponds to an earthquake of magnitude M= 4.9. This is an area where
earthquakes usually have focal mechanisms of the reverse type [
58
]. For the far-field

Sustainability 2022,14, 15976 8 of 24
scenario, the coordinates of the abovementioned earthquake were adopted (Figure 4). The
rupture plane dimensions were obtained according to an empirical expression [
59
]. The
adopted azimuth of the fault was equal to 244.5
◦
and the dip angle was 64
◦
. The primary
school that is closest to the epicentre is in Portugal (Escola Básica de Ilha da Culatra) at an
epicentre distance of 47.1 km. Near the border, the school that is closest to the rupture is in
Spain (Colegio Virgen del Carmen) at 43.3 km from the fault plane.
Sustainability 2022, 14, x FOR PEER REVIEW 9 of 26
According to the Spanish IGN [57] (Instituto Geográfico Nacional) earthquake cata-
logue, an earthquake of a magnitude greater than 4.5 (happening in this offshore area after
1961) occurred on 3 January, 2005, with an epicentre located at latitude 36.6161° and lon-
gitude −7.5947°. This corresponds to an earthquake of magnitude M = 4.9. This is an area
where earthquakes usually have focal mechanisms of the reverse type [58]. For the far-
field scenario, the coordinates of the abovementioned earthquake were adopted (Figure
4). The rupture plane dimensions were obtained according to an empirical expression [59].
The adopted azimuth of the fault was equal to 244.5° and the dip angle was 64°. The pri-
mary school that is closest to the epicentre is in Portugal (Escola Básica de Ilha da Culatra)
at an epicentre distance of 47.1 km. Near the border, the school that is closest to the rupture
is in Spain (Colegio Virgen del Carmen) at 43.3 km from the fault plane.
Figure 4. Earthquake scenario with magnitude M = 7.7 located in a possible offshore source [55].
This is identified near the border between the Algarve (left side of yellow border line) and Huelva
(right side of yellow border line) regions.
The largest onshore earthquake recorded after 1961 that exists in the IGN catalogue
occurred on 20 December 1989. This occurred at a latitude of 37.225° and a longitude of
−7.3917°, with a depth of 23 km and a magnitude of M = 5.0. In this area, earthquakes
normally present strike–slip focal mechanisms [58]. The closest primary school to the ep-
icentre is in Spain (Colegio Galdames) at about 1.2 km. Thus, this location seems to be quite
good for establishing the near-source earthquake scenario for the present study, with a
magnitude of M = 5.2. A strike–slip rupture was adopted, with a focal depth of 13 km and
a vertical plane aligned with the Guadiana River (Figure 5).
Figure 4.
Earthquake scenario with magnitude M= 7.7 located in a possible offshore source [
55
]. This
is identified near the border between the Algarve (left side of yellow border line) and Huelva (right
side of yellow border line) regions.
The largest onshore earthquake recorded after 1961 that exists in the IGN catalogue
occurred on 20 December 1989. This occurred at a latitude of 37.225
◦
and a longitude of
−
7.3917
◦
, with a depth of 23 km and a magnitude of M = 5.0. In this area, earthquakes
normally present strike–slip focal mechanisms [
58
]. The closest primary school to the
epicentre is in Spain (Colegio Galdames) at about 1.2 km. Thus, this location seems to be
quite good for establishing the near-source earthquake scenario for the present study, with
a magnitude of M = 5.2. A strike–slip rupture was adopted, with a focal depth of 13 km
and a vertical plane aligned with the Guadiana River (Figure 5).
Sustainability 2022, 14, x FOR PEER REVIEW 10 of 26
Figure 5. Earthquake scenario with magnitude M = 5.2 near the borderline (in yellow) between the
Algarve (left side) and Huelva (right side) regions. It has the same epicentre as the 20 of December
of 1989 earthquake (M = 5.0) according to the IGN catalogue.
2.3. Vulnerability Evaluation
As mentioned in the introduction, there are several possible approaches for assessing
the seismic vulnerability of existing schools. The objectives of the PERSISTAH project
were to analyse the seismic safety of these buildings according to the legal framework of
both regions under study and to rank the seismic risk of school buildings for seismic ret-
rofitting purposes. Therefore, it was opted to apply the seismic structural analysis meth-
odologies presented in Part 3 of Eurocode 8 (EC8-3) [60], considering the limit states (LS)
established for the Algarve in the NP EN 1998-3:2017 [61]. These are usually adopted for
the seismic assessment of a single building. However, in this case, they were applied to a
large number of school buildings throughout the development of the computer routines
that were developed to automatically carry out this task [43] as if each building were an-
alysed individually. From all the different seismic analysis approaches proposed in the
EC8-3, nonlinear static seismic analyses were selected. First, a different software was used
to perform nonlinear static analyses to compute the capacity curves of each school build-
ing following the requirements of the EC8-3 (12 for each building, in most cases). These
capacity curves were then imported into the PERSISTAH software to rank the seismic
safety of the school buildings according to different possible seismic actions.
2.3.1. Capacity Curves Obtained for the Algarve Region (Portugal)
Regarding the Algarve region, particular attention was given to the unreinforced ma-
sonry (URM) school buildings that were built before the first Portuguese seismic codes.
The capacity curves of these buildings were determined according to the principles and
rules defined in the EC8-3 [47], using the TreMuri software [62]. In the case of RC schools
built in the early 1990s, it was not possible to check the safety levels currently required in
the NP EN 1998-3:2017 for all the LS. As concluded in [63], the level of seismic vulnerabil-
ity of this type of structure seems to be much lower and much less worrying. However,
RC buildings designed before the 1983 Portuguese code, namely the so-called “P3”
schools [48], present low shear reinforcement ratios in their columns. For these buildings,
the nonlinear structural analyses were carried out with Seismostruct [64]. The results
show premature shear failures. In this case, as already carried out in earlier studies [65]
and considering the civil protection purposes, a residual shear strength of the columns
was adopted to reproduce the expected degree of damage for higher displacement values.
Figure 5.
Earthquake scenario with magnitude M= 5.2 near the borderline (in yellow) between the
Algarve (left side) and Huelva (right side) regions. It has the same epicentre as the 20 of December of
1989 earthquake (M= 5.0) according to the IGN catalogue.

Sustainability 2022,14, 15976 9 of 24
2.3. Vulnerability Evaluation
As mentioned in the introduction, there are several possible approaches for assessing
the seismic vulnerability of existing schools. The objectives of the PERSISTAH project
were to analyse the seismic safety of these buildings according to the legal framework
of both regions under study and to rank the seismic risk of school buildings for seismic
retrofitting purposes. Therefore, it was opted to apply the seismic structural analysis
methodologies presented in Part 3 of Eurocode 8 (EC8-3) [
60
], considering the limit states
(LS) established for the Algarve in the NP EN 1998-3:2017 [
61
]. These are usually adopted
for the seismic assessment of a single building. However, in this case, they were applied to
a large number of school buildings throughout the development of the computer routines
that were developed to automatically carry out this task [
43
] as if each building were
analysed individually. From all the different seismic analysis approaches proposed in
the EC8-3, nonlinear static seismic analyses were selected. First, a different software was
used to perform nonlinear static analyses to compute the capacity curves of each school
building following the requirements of the EC8-3 (12 for each building, in most cases).
These capacity curves were then imported into the PERSISTAH software to rank the seismic
safety of the school buildings according to different possible seismic actions.
2.3.1. Capacity Curves Obtained for the Algarve Region (Portugal)
Regarding the Algarve region, particular attention was given to the unreinforced
masonry (URM) school buildings that were built before the first Portuguese seismic codes.
The capacity curves of these buildings were determined according to the principles and
rules defined in the EC8-3 [
47
], using the TreMuri software [
62
]. In the case of RC schools
built in the early 1990s, it was not possible to check the safety levels currently required in
the NP EN 1998-3:2017 for all the LS. As concluded in [
63
], the level of seismic vulnerability
of this type of structure seems to be much lower and much less worrying. However, RC
buildings designed before the 1983 Portuguese code, namely the so-called “P3” schools [
48
],
present low shear reinforcement ratios in their columns. For these buildings, the nonlinear
structural analyses were carried out with Seismostruct [
64
]. The results show premature
shear failures. In this case, as already carried out in earlier studies [
65
] and considering
the civil protection purposes, a residual shear strength of the columns was adopted to
reproduce the expected degree of damage for higher displacement values.
2.3.2. Capacity Curves Obtained for the Huelva Region (Spain)
In the case of Huelva, the seismic assessment of the buildings was carried out according
to the performance-based method. In a similar way to the Algarve, the seismic safety was
verified according to the EC8 requirements. The capacity of the buildings was obtained
according to different numerical modelling procedures. The seismic hazard was acquired
according to the seismic code in Spain (NCSE-02) [
50
] and the Spanish update of the ground
acceleration values [66].
For URM buildings, the TreMuri software was also used. In [
67
], the optimal seismic
retrofitting of a URM case study was analysed. It was representative of the URM buildings
identified in the area. It was found that this case presents a probability of “collapse” and of
“severe damage” of 45% and 40%, respectively. Furthermore, it presented a very low ductile
behaviour. It was concluded that the most effective solutions (according to a cost–benefit
analysis) were the addition of encirclements with L-shape profiles and steel grids spaced at
certain distances.
The seismic assessment was mainly focused on RC buildings. This was due to the
amount of them and to the available data at different local archives (such as blueprints
and reports). Different software was used to numerically model the buildings, focusing on
the use of OpenSees [
68
]. The ageing effects of the RC frames, the infills, the irregularities
in plans and in height or the presence of smooth rebar were considered in the analyses,
as presented in [
69
]. The soil–structure interaction effects have also been tested [
70
]. It
was found that they can worsen the capacity of the medium-rise buildings up to 10%.

Sustainability 2022,14, 15976 10 of 24
Additionally, the seismic retrofitting of different case study buildings representative of
different typologies has been analysed. Further information on the seismic assessment of
the buildings can be found in [49].
2.4. Ranking School Buildings
Given that funding is usually limited, it is important to establish seismic safety rank-
ings to identify the buildings with a higher risk. This can be obtained according to the
seismic hazard of the site and the vulnerability of the buildings. This type of analyses is
especially important to set the different seismic retrofitting intervention priorities and in
relation to higher importance classes [
71
]. Schools are one of those groups of buildings
for which different types of rankings were suggested, usually based on the ratios between
capacity and demand associated with a certain LS [72].
In the PERSISTAH project, a similar procedure was adopted to rank the schools.
In this case, the adopted school score corresponds to the expression presented below
(Equation (2)). This was implemented in the software developed. This score
(scoreLS )
is
inversely proportional to the percentage of the seismic action
(%Se,LS)
, associated with
a given LS, defined from the seismic performance [
43
]. If the reference seismic action is
the response spectrum established in the EC8-1, then this corresponds to the inverse of
the coefficient
(γLS)
[
47
]. This should multiply the seismic action corresponding to the
reference return period.
scoreLS =100
%Se,LS
=1
γLS
(2)
The LS might be a life-saving LS, which is related to the LS of significant damage (SD)
of the EC8-3, or to the collapse LS, which is related to the LS of near collapse (NC) of the
EC8-3. It can also be any other LS related to full operational performance (OP) or damage
limitation (DL), depending on the goal of the study. The higher the score, the higher the
seismic risk and, therefore, seismic retrofitting interventions are more needed.
Further studies would consider other important variables to define a more complex
but more realistic score, in linking educational facilities and those essential utilities, such
as power, water, and sewers, to be available for the functionality of school systems after
disasters [73].
A set of factors that affect the functionality of schools includes the performance of non-
structural elements, the number of students in each school and the difficulty in assessing
the school. The decision to reopen schools after disasters involves not only the school
building, the school administrators or staff, but also the damage to community buildings
and infrastructure after an earthquake. A multi-criteria approach can be helpful for the
construction of a global school score.
3. Retrofitting of Pilot School Buildings
The seismic retrofitting of school buildings has received particular international at-
tention [
74
–
82
]. After identifying the schools with the highest score in the ranking, it is
necessary to select a set of retrofitting strategies. These depend on the type of existing
structural system and its dynamic characteristics. They also depend on the ratio between
the seismic demand and the capacity of the structure.
In regions where there is no tradition of seismic retrofitting, it is very important to
train technicians to carry out the task. In this context, one of the goals of the PERSISTAH
project was to perform the seismic retrofitting interventions of two pilot schools. To do so,
one school in the Algarve region (Portugal) and another in the Huelva region (Spain) were
selected so that they could serve as examples for the two studied regions. The selection
of the schools was made based on their school score and the money allocated for the task.
Finally, two small masonry school buildings were chosen.

Sustainability 2022,14, 15976 11 of 24
3.1. The Brancanes Primary School (Olhão, Algarve, Portugal)
As aforementioned, one of the typologies of masonry schools that still abound in
the Algarve is the schools designed by the architect Fernando Peres. The Brancanes
primary school is one of those schools (FP2 [
47
]). It has a single storey. Sometime after its
construction, a new space was added. This new building was separated from the original
construction and possesses an RC structure. The original classrooms have two independent
entrances because the school was built in 1961, when there was still a gender separation in
Portugal. The masonry walls, which support an RC slab, are made of limestone from the
region and lime–sand mortar.
The structural analysis of the original masonry building indicated that the school did
not have the appropriate level of seismic safety [
83
]. The adopted retrofitting solution
consisted of wall jacketing (Figure 6). Two layers of pre-mixed lime mortar were applied
to the opposite faces of the walls. These were connected by means of transverse inox ties
through the masonry, as proposed in the EC8-3. The selection of lime-based mortar, instead
of cement mortar or concrete, aimed to ensure the physical, chemical, and mechanical
compatibility of the new material with the existing one. The choice of inox ties was due to
durability issues.
Sustainability 2022, 14, x FOR PEER REVIEW 12 of 26
A set of factors that affect the functionality of schools includes the performance of
non-structural elements, the number of students in each school and the difficulty in as-
sessing the school. The decision to reopen schools after disasters involves not only the
school building, the school administrators or staff, but also the damage to community
buildings and infrastructure after an earthquake. A multi-criteria approach can be helpful
for the construction of a global school score.
3. Retrofitting of Pilot School Buildings
The seismic retrofitting of school buildings has received particular international at-
tention [74–82]. After identifying the schools with the highest score in the ranking, it is
necessary to select a set of retrofitting strategies. These depend on the type of existing
structural system and its dynamic characteristics. They also depend on the ratio between
the seismic demand and the capacity of the structure.
In regions where there is no tradition of seismic retrofitting, it is very important to
train technicians to carry out the task. In this context, one of the goals of the PERSISTAH
project was to perform the seismic retrofitting interventions of two pilot schools. To do
so, one school in the Algarve region (Portugal) and another in the Huelva region (Spain)
were selected so that they could serve as examples for the two studied regions. The selec-
tion of the schools was made based on their school score and the money allocated for the
task. Finally, two small masonry school buildings were chosen.
3.1. The Brancanes Primary School (Olhão, Algarve, Portugal)
As aforementioned, one of the typologies of masonry schools that still abound in the
Algarve is the schools designed by the architect Fernando Peres. The Brancanes primary
school is one of those schools (FP2 [47]). It has a single storey. Sometime after its construc-
tion, a new space was added. This new building was separated from the original construc-
tion and possesses an RC structure. The original classrooms have two independent en-
trances because the school was built in 1961, when there was still a gender separation in
Portugal. The masonry walls, which support an RC slab, are made of limestone from the
region and lime–sand mortar.
The structural analysis of the original masonry building indicated that the school did
not have the appropriate level of seismic safety [83]. The adopted retrofitting solution con-
sisted of wall jacketing (Figure 6). Two layers of pre-mixed lime mortar were applied to
the opposite faces of the walls. These were connected by means of transverse inox ties
through the masonry, as proposed in the EC8-3. The selection of lime-based mortar, in-
stead of cement mortar or concrete, aimed to ensure the physical, chemical, and mechan-
ical compatibility of the new material with the existing one. The choice of inox ties was
due to durability issues.
Figure 6. Retrofitting solution that was adopted at the Brancanes primary school (Olhão, Algarve,
Portugal).
Figure 6.
Retrofitting solution that was adopted at the Brancanes primary school (Olhão, Algarve, Portugal).
3.2. The Los Lanos Primary School (Almonte, Huelva, Spain)
The building selected for retrofitting is a small URM two-storey building built in the
1980s. The walls are 25 cm thick, with rigid RC floors. It has a sloped tiled roof and shallow
concrete foundations. The openings on the façade are located on the longitudinal walls,
while the walls in the orthogonal direction are blind (Figure 7).
Sustainability 2022, 14, x FOR PEER REVIEW 13 of 26
3.2. The Los Lanos Primary School (Almonte, Huelva, Spain)
The building selected for retrofitting is a small URM two-storey building built in the
1980s. The walls are 25 cm thick, with rigid RC floors. It has a sloped tiled roof and shallow
concrete foundations. The openings on the façade are located on the longitudinal walls,
while the walls in the orthogonal direction are blind (Figure 7).
Its vulnerability evaluation was performed as explained in Section 2.3, resulting in
one of the highest school scores of the area studied. Moreover, the building does not com-
ply with the seismic code requirements. The uneven distributed openings represent the
main seismic weakness of the building. The probability of severe and complete damage
in its weak direction is quite high.
Therefore, the search for retrofitting solutions focused on the mitigation of the weak
direction openings’ effect and, thus, the reinforcement of the façade walls. Three potential
solutions were considered: external wire mesh, carbon fibre-reinforced polymer (CFRP)
mesh and steel rebars around openings. They were selected based on the following fea-
tures: (i) easy execution from the outside of the building, (ii) low cost/effectiveness ratio,
(iii) low/no architectural impact and, of course, (iv) improvement of the seismic behaviour
of the building.
This last feature was studied following the method described in Section 2.3, finding
that the retrofitted models outperform the as-built one. A higher resistance capacity and
a notable reduction in the target displacement at the performance point for all of them
was obtained.
In particular, the larger improvement was provided by the combination of two of the
methods (Figure 8): the application of an external steel mesh on the façade walls plus the
reinforcement of the openings by means of rebars. The analysis of this solution showed
that it increases the global stiffness of the structure, reducing deformations. The steel mesh
provides an increase in the maximum strength, while the rebars at the openings contribute
to a reduction in the displacement at the performance point. The CFRP technique, by con-
trast, showed the worst improvement/cost ratio and was, therefore, disregarded.
Figure 7. Long façade after retrofitting.
The combination of the steel mesh and rebar around the openings was implemented.
A 20 × 20 cm Ø8 mm mesh was put on the external walls and 2 Ø8 mm rebars were hung
around each opening. The solution was quickly and easily implemented by a regular local
firm, with no special training. It was relatively cheap, and both the aesthetics and the
functionality of the building remained unchanged.
Figure 7. Long façade after retrofitting.

Sustainability 2022,14, 15976 12 of 24
Its vulnerability evaluation was performed as explained in Section 2.3, resulting in one
of the highest school scores of the area studied. Moreover, the building does not comply
with the seismic code requirements. The uneven distributed openings represent the main
seismic weakness of the building. The probability of severe and complete damage in its
weak direction is quite high.
Therefore, the search for retrofitting solutions focused on the mitigation of the weak
direction openings’ effect and, thus, the reinforcement of the façade walls. Three potential
solutions were considered: external wire mesh, carbon fibre-reinforced polymer (CFRP)
mesh and steel rebars around openings. They were selected based on the following
features: (i) easy execution from the outside of the building, (ii) low cost/effectiveness ratio,
(iii) low/no architectural impact and, of course, (iv) improvement of the seismic behaviour
of the building.
This last feature was studied following the method described in Section 2.3, finding
that the retrofitted models outperform the as-built one. A higher resistance capacity and
a notable reduction in the target displacement at the performance point for all of them
was obtained.
In particular, the larger improvement was provided by the combination of two of the
methods (Figure 8): the application of an external steel mesh on the façade walls plus the
reinforcement of the openings by means of rebars. The analysis of this solution showed
that it increases the global stiffness of the structure, reducing deformations. The steel mesh
provides an increase in the maximum strength, while the rebars at the openings contribute
to a reduction in the displacement at the performance point. The CFRP technique, by
contrast, showed the worst improvement/cost ratio and was, therefore, disregarded.
Sustainability 2022, 14, x FOR PEER REVIEW 14 of 26
Figure 8. Construction detail of the reinforcement used.
4. Risk Communication
It has been observed that populations are not aware of buildings’ seismic risk, even
in societies that have modern seismic codes and where earthquakes are frequent. It has
been found that even in seismic-prone countries such as Chile, expectations about the
seismic behaviour of constructions have been unrealistic [84]. Populations should be
aware that, even if a building meets all the seismic safety requirements established in a
modern code, they are not designed to withstand earthquakes without damage. Moreo-
ver, it may even be economically unfeasible to repair it after a very intense earthquake.
The primary goal of a well-designed structure is related to life safety issues. Depending
on the seismic code, a moderate earthquake can cause moderate or severe damage mainly
of the non-structural elements. This might affect the operation of the facilities for a long
time.
In this context, it is important to promote education of and information for the pop-
ulation to contribute to increasing the resilience of the society to these natural phenomena.
The school context seems to be an important vehicle to achieve this goal. Moreover, school
buildings also suffer the effects of earthquakes. Given the high concentration of children
and young people in schools and the fact that they spend a large part of their time in
school, the consequences of any structural and non-structural failure could be fatal for
them.
Schools play a key role in supporting their communities after an earthquake. Teach-
ers, principals, and non-teaching staff assume roles that go beyond educational leader-
ship. They must deal with an immediate crisis, running schools as community centres
after the disaster. Moreover, they must be sensitive to the physical, emotional, social and
psychological needs of their students and families [16].
The positive effect of educational programmes on children affected by a very destruc-
tive earthquake is known [85]. So that teachers, monitors and technicians in the educa-
tional area can fulfil this goal, it is necessary for them to have pedagogical and didactic
resources for the initial and continued training of the school community. Given the lack
of this material in the regions under study, the Why does the ground shake? [86] and Practical
guide for earthquake resilient schools [87] guides were created, which are available in three
different languages (Portuguese, Spanish and English). These tools can be used in three
types of learning (formal, non-formal and informal). This way, it facilitates the intercon-
nection between the learning of the subjects and the domains of the primary school cur-
riculum. Thus, it is intended to teach educators and children about the seismic phenome-
non and the reduction of risk, in a creative, pedagogical, and playful way. Therefore, var-
ious activities that promote individual and collective participation were integrated. In this
Figure 8. Construction detail of the reinforcement used.
The combination of the steel mesh and rebar around the openings was implemented.
A 20
×
20 cm Ø8 mm mesh was put on the external walls and 2 Ø8 mm rebars were hung
around each opening. The solution was quickly and easily implemented by a regular local
firm, with no special training. It was relatively cheap, and both the aesthetics and the
functionality of the building remained unchanged.
4. Risk Communication
It has been observed that populations are not aware of buildings’ seismic risk, even in
societies that have modern seismic codes and where earthquakes are frequent. It has been
found that even in seismic-prone countries such as Chile, expectations about the seismic
behaviour of constructions have been unrealistic [
84
]. Populations should be aware that,
even if a building meets all the seismic safety requirements established in a modern code,
they are not designed to withstand earthquakes without damage. Moreover, it may even

Sustainability 2022,14, 15976 13 of 24
be economically unfeasible to repair it after a very intense earthquake. The primary goal of
a well-designed structure is related to life safety issues. Depending on the seismic code, a
moderate earthquake can cause moderate or severe damage mainly of the non-structural
elements. This might affect the operation of the facilities for a long time.
In this context, it is important to promote education of and information for the popu-
lation to contribute to increasing the resilience of the society to these natural phenomena.
The school context seems to be an important vehicle to achieve this goal. Moreover, school
buildings also suffer the effects of earthquakes. Given the high concentration of children
and young people in schools and the fact that they spend a large part of their time in school,
the consequences of any structural and non-structural failure could be fatal for them.
Schools play a key role in supporting their communities after an earthquake. Teachers,
principals, and non-teaching staff assume roles that go beyond educational leadership. They
must deal with an immediate crisis, running schools as community centres after the disaster.
Moreover, they must be sensitive to the physical, emotional, social and psychological needs
of their students and families [16].
The positive effect of educational programmes on children affected by a very destruc-
tive earthquake is known [
85
]. So that teachers, monitors and technicians in the educational
area can fulfil this goal, it is necessary for them to have pedagogical and didactic resources
for the initial and continued training of the school community. Given the lack of this
material in the regions under study, the Why does the ground shake? [
86
] and Practical guide
for earthquake resilient schools [
87
] guides were created, which are available in three different
languages (Portuguese, Spanish and English). These tools can be used in three types of
learning (formal, non-formal and informal). This way, it facilitates the interconnection
between the learning of the subjects and the domains of the primary school curriculum.
Thus, it is intended to teach educators and children about the seismic phenomenon and the
reduction of risk, in a creative, pedagogical, and playful way. Therefore, various activities
that promote individual and collective participation were integrated. In this way, a culture
of safety is developed in children so that they can transfer it to other moments of their daily
lives and to the general population. In this context, special attention was given to problems
related to non-structural elements, namely in the guides that were created [
87
], where
issues related to the preparation activities that it is possible to carry out were focused on.
The educational guide Why does the ground shake? was tested and implemented from
the beginning of the PERSISTAH project, namely, it was used with students from pre-school
(five-years-old) and primary education (6 to 12-years-old). Two training courses for teachers
were also held in Almonte (Huelva, Spain) and in Olhão (Algarve, Portugal). This allowed
us to test the methodology and prove its practical success (Figure 9).
Sustainability 2022, 14, x FOR PEER REVIEW 15 of 26
way, a culture of safety is developed in children so that they can transfer it to other mo-
ments of their daily lives and to the general population. In this context, special attention
was given to problems related to non-structural elements, namely in the guides that were
created [87], where issues related to the preparation activities that it is possible to carry
out were focused on.
The educational guide Why does the ground shake? was tested and implemented from
the beginning of the PERSISTAH project, namely, it was used with students from pre-
school (five-years-old) and primary education (6 to 12-years-old). Two training courses
for teachers were also held in Almonte (Huelva, Spain) and in Olhão (Algarve, Portugal).
This allowed us to test the methodology and prove its practical success (Figure 9).
Figure 9. Activity carried out with the teachers based on the educational guide Why does the ground
shake?.
Recently, during the COVID-19 pandemic lockdown, it was possible to use the Why
does the ground shake? educational material and participate in the Portuguese programme
#EstudoEmCasa, aimed at students from the 1st to the 9th grade [88]. The TV programme
was broadcasted on RTP Memória, RTP Internacional and RTP Play.
5. Results and Discussion
One of the main difficulties of the PERSISTAH project was to establish the earth-
quake scenarios of many schools spread over the two neighbouring countries. This is a
very challenging task. On the one hand, it is challenging because the scenario should be
plausible, and the earthquake should take place in areas with well-known seismic sources.
This is very complex when dealing with offshore seismic sources. On the other hand, it is
challenging because, if the results are accessible to everyone, they may generate panic in
the school community without absolute certainty concerning the occurrence of those sce-
narios. In this context, it is very important to validate the results properly. This can be
done by comparing them with identical scenarios that occurred in the region studied or,
when that information does not exist, in other regions of the world. Unfortunately, even
though the Algarve–Huelva region has been affected by several destructive earthquakes
throughout its history [89,90], no instrumental records have yet been obtained in the re-
gion regarding a major destructive earthquake.
The 28 February 1969 (Ms = 8) earthquake caused the collapse of some buildings in
the Algarve (masonry buildings). However, the rupture was very distant and only one
Figure 9.
Activity carried out with the teachers based on the educational guide Why does the ground shake?

Sustainability 2022,14, 15976 14 of 24
Recently, during the COVID-19 pandemic lockdown, it was possible to use the Why
does the ground shake? educational material and participate in the Portuguese programme
#EstudoEmCasa, aimed at students from the 1st to the 9th grade [
88
]. The TV programme
was broadcasted on RTP Memória, RTP Internacional and RTP Play.
5. Results and Discussion
One of the main difficulties of the PERSISTAH project was to establish the earthquake
scenarios of many schools spread over the two neighbouring countries. This is a very
challenging task. On the one hand, it is challenging because the scenario should be
plausible, and the earthquake should take place in areas with well-known seismic sources.
This is very complex when dealing with offshore seismic sources. On the other hand, it
is challenging because, if the results are accessible to everyone, they may generate panic
in the school community without absolute certainty concerning the occurrence of those
scenarios. In this context, it is very important to validate the results properly. This can be
done by comparing them with identical scenarios that occurred in the region studied or,
when that information does not exist, in other regions of the world. Unfortunately, even
though the Algarve–Huelva region has been affected by several destructive earthquakes
throughout its history [
89
,
90
], no instrumental records have yet been obtained in the region
regarding a major destructive earthquake.
The 28 February 1969 (Ms = 8) earthquake caused the collapse of some buildings in
the Algarve (masonry buildings). However, the rupture was very distant and only one
strong motion record was obtained in a station located in Lisbon [
91
], very far away from
the earthquake source.
Given the evaluation method adopted [
43
], it is necessary to use GMPEs that present
spectral values and not only peak ground acceleration (PGA) values. Unfortunately, there
are no such GMPEs established for this region based on earthquake records.
It is important to emphasise that the purpose of this study is not to validate the
scenarios defined in Section 2.2.2, whose magnitudes are established in the Portuguese
National Annex of the EC8-5, but the possible damage effects of these scenarios. Thus, the
choice of which GMPE to use is of utmost importance. It should reproduce the spectral
values that the earthquakes may generate in the various study sites. Moreover, there might
be some unexpected results, concerning both high and small-magnitude earthquake events,
which are not captured by some GMPEs. This is due to the incomplete knowledge of how
all the factors that influence the level of vibration in a given place come together [92].
There are multiple GMPEs that are proposed by different authors, but not all of them
were established with earthquakes that cover the range of magnitudes and distances that are
required for this study. Some GMPEs adopt the epicentral distance, others the hypocentral
distance, others the Joyner–Boore distance, and others the closest distance to the rupture
plane, or a combination of some or all of them [93].
For large magnitudes, as is the case of the far-field earthquake scenario presented in
Section 2.2.2, the dimension of the rupture may be very large, so it might not be rigorous to
use the epicentral distance or the hypocentral distance. To better understand the impact on
the results of this issue, an analysis of the effects of the onshore Amberley (New Zealand)
Earthquake of 13 November 2016 (magnitude Mw = 7.8) was carried out. This was done by
consulting the acceleration records that exist in the “Center for Engineering Strong Motion
Data” [
94
], recorded in stations from the GNS network. If we analyse the records obtained
in the Seddon Fire Station (SEDS), located at an epicentral distance of 145.3 km, but just
23.0 km from the fault, it is possible to see that the PGA was 0.759 g, which is a high value
for such a long epicentral distance (probably due to the proximity to the rupture). However,
in the Lake Taylor Station (LTZ), at a closer distance to the epicentre (64.3 km), but at a
farther distance from the fault (52.8 km), the PGA was just 0.094 g. Obviously, this might
be also due to site effects or to the relative distance to existing fault asperities, and not only
to the distance from the fault. However, this phenomenon can also be observed in other
stations, such as the Blenheim Marlborough Girls (MGCS), for which the soil characteristics

Sustainability 2022,14, 15976 15 of 24
are known (V
s30
= 210 m/s) [
95
]. This is located at an epicentral distance of 155.1 km, but
only at 42.7 km from the fault, and presented a PGA of 0.269 g. Moreover, the importance
of the distance to the ruptured fault plane can also be observed in other earthquakes, or
through the results of stochastic simulations [
44
]. This type of comparison was also carried
out by another author for Nepal, in the context of the Gorkha earthquake (Mw = 7.8) that
occurred on 25 April 2015 [
96
]. This means that the distance to the fault plane rupture
seems to be a better choice, regarding accuracy issues, when selecting a GMPE to deal
with high-magnitude earthquake events. For this reason, an attempt was made to find
a GMPE that is a function of the shortest distance to the rupture (R
RUP
), for computing
the response spectrum of each school site. This type of GMPE is more complex to use
because more parameters are needed. In addition, this is more difficult to implement in
software, but it seems to be more accurate [
97
]. In this type of more general mathematical
expression (Equation (3)), the spectral acceleration
(Sa(T))
is a function of the period (T)
and of all, or just part, of the following parameters: the earthquake magnitude
(fM(T))
; the
distance to the source
(fR(T))
, which depends on the adopted GMPE, which considers both
geometrical and anelastic attenuation; the type of the earthquake fault
(fF(T))
; a hanging
wall term
(fH(T))
; a fault dip term
(fD(T))
; the site geologic conditions
(fS(T))
, usually a
function of the VS30 value; and a basin response term (fB(T)).
ln Sa(T)=fM(T)+fR(T)+fF(T)+fH(T)+fD(T)+fS(T)+fB(T). (3)
To better understand the accuracy that we can expect for the selected damage scenarios,
the results of the GMPEs [
98
–
103
] that were implemented in the developed software
were first compared with response spectra obtained from earthquake records. The first
set was recorded in the CHBH14 (V
s30
= 201 m/s, ground type C of the EC8-1, focus
distance of 72 km) and in the IBRH18 (V
s30
= 559 m/s, ground type B of the EC8-1, focus
distance of 78 km) Japanese stations of the KiK-net [
104
]. This network provides records
obtained at the bedrock level and at the surface and presents much information about the
geological characteristics of the sites. The 11 March 2011 earthquake (JMA magnitude of
7.7, Mw = 7.8), which was an aftershock of the great Tohoku Earthquake (Mw = 9.0) [105],
was considered. This offshore earthquake and those station sites were chosen because the
earthquake mechanism and the relative position of those sites regarding the fault rupture
have some similarities to the context of the earthquake scenario presented in Figure 4. For
this sensitivity analysis, it was assumed that the focus was placed on the middle of the
fault plane, and the NIED earthquake mechanism was adopted (strike equal to 209
◦
and
dip equal to 31
◦
, which are close to the mainshock values [
106
]). The comparison of the
results is presented in Figure 10, only using the implemented GMPEs [
100
–
103
] that are
valid for earthquakes up to M= 7.8.
When analysing the response spectra shown in Figure 10, it is possible to conclude
that the GMPE presenting the highest spectral values is the one that was established for
the Chilean subduction area [
102
]. For the CHBH14 site, the values are too high, but for
the IBRH18 site, this is the only GMPE that presents results close to the recorded ones.
All the other GMPEs exhibit much lower values when compared with the records. Those
differences might be due to the possibility of the fault plane not being centred in the focus,
which might increase, or decrease, the closest distance from the rupture. Other factors such
as the relative distance from fault asperities and the geological site effects are also factors
that can influence the response spectra shape and, consequently, the building damage, as
shown in previous studies [107].
The offshore area that is close to the Algarve and Huelva regions where the M= 7.7
earthquake rupture was placed is not a subduction area, so it is questionable to use GMPEs
that are obtained in subduction areas. Nevertheless, the region studied is not very far from
the subduction zone below the Gibraltar Arc [
108
], so these GMPEs were tested in this
study as well.

Sustainability 2022,14, 15976 16 of 24
Sustainability 2022, 14, x FOR PEER REVIEW 17 of 26
𝑙𝑛 𝑆() =
𝑓
()
𝑓
()
𝑓
()
𝑓
()
𝑓
()
𝑓
()
𝑓
(). (3)
To better understand the accuracy that we can expect for the selected damage scenar-
ios, the results of the GMPEs [98–103] that were implemented in the developed software
were first compared with response spectra obtained from earthquake records. The first set
was recorded in the CHBH14 (V
s30
= 201 m/s, ground type C of the EC8-1, focus distance
of 72 km) and in the IBRH18 (V
s30
= 559 m/s, ground type B of the EC8-1, focus distance of
78 km) Japanese stations of the KiK-net [104]. This network provides records obtained at
the bedrock level and at the surface and presents much information about the geological
characteristics of the sites. The 11 March 2011 earthquake (JMA magnitude of 7.7, Mw =
7.8), which was an aftershock of the great Tohoku Earthquake (Mw = 9.0) [105], was con-
sidered. This offshore earthquake and those station sites were chosen because the earth-
quake mechanism and the relative position of those sites regarding the fault rupture have
some similarities to the context of the earthquake scenario presented in Figure 4. For this
sensitivity analysis, it was assumed that the focus was placed on the middle of the fault
plane, and the NIED earthquake mechanism was adopted (strike equal to 209° and dip
equal to 31°, which are close to the mainshock values [106]). The comparison of the results
is presented in Figure 10, only using the implemented GMPEs [100–103] that are valid for
earthquakes up to M = 7.8.
When analysing the response spectra shown in Figure 10, it is possible to conclude
that the GMPE presenting the highest spectral values is the one that was established for
the Chilean subduction area [102]. For the CHBH14 site, the values are too high, but for
the IBRH18 site, this is the only GMPE that presents results close to the recorded ones. All
the other GMPEs exhibit much lower values when compared with the records. Those dif-
ferences might be due to the possibility of the fault plane not being centred in the focus,
which might increase, or decrease, the closest distance from the rupture. Other factors
such as the relative distance from fault asperities and the geological site effects are also
factors that can influence the response spectra shape and, consequently, the building dam-
age, as shown in previous studies [107].
Figure 10. Comparison of the response spectra obtained with several GMPEs for the offshore sce-
nario, the Japan earthquake records (Mw = 7.8), and the seismic actions of the Portuguese (type 1 of
the NP EN 1998-1:2010
[46]
for Vila Real de Santo António) and for the Spanish (NCSE-02
[50]
for
Ayamonte) seismic codes, which are currently mandatory for each region: (a) for the CHBH14 site
(ground type C) and (b) for the IBRH18 site (ground type B) [100–103].
The offshore area that is close to the Algarve and Huelva regions where the M = 7.7
earthquake rupture was placed is not a subduction area, so it is questionable to use
GMPEs that are obtained in subduction areas. Nevertheless, the region studied is not very
far from the subduction zone below the Gibraltar Arc [108], so these GMPEs were tested
in this study as well.
(a) (b)
Figure 10.
Comparison of the response spectra obtained with several GMPEs for the offshore scenario,
the Japan earthquake records (Mw = 7.8), and the seismic actions of the Portuguese (type 1 of the NP
EN 1998-1:2010 [
46
] for Vila Real de Santo António) and for the Spanish (NCSE-02 [
50
] for Ayamonte)
seismic codes, which are currently mandatory for each region: (
a
) for the CHBH14 site (ground
type C) and (b) for the IBRH18 site (ground type B) [100–103].
This strategy was also adopted to assess the ability of the implemented GMPEs to
reproduce near-field earthquake scenarios (in this case, the GMPEs that were developed for
subduction areas were not used). A superficial onshore earthquake that occurred in Japan
on 21 September, 2011 (JMA magnitude of 5.2, Mw = 5.1) was selected. This earthquake was
recorded in two very close sites of the KiK-net network: the IBRH13 site (V
s30
= 335 m/s,
ground type C of the EC8-1, focus distance of 10.8 km) and the IBRH14 site (V
s30
= 829 m/s,
ground type A of the EC8-1, focus distance of 10.3 km). These records presented PGA values
which are close to the ones obtained in Spain after the 2011 Lorca earthquake [
109
]. For
this scenario, two of the adopted GMPEs use the closest distance to the rupture [
100
,
101
].
The other two use the Joyner–Boore distance [
98
,
99
]. The comparative results are presented
in Figure 11.
Sustainability 2022, 14, x FOR PEER REVIEW 18 of 26
This strategy was also adopted to assess the ability of the implemented GMPEs to
reproduce near-field earthquake scenarios (in this case, the GMPEs that were developed
for subduction areas were not used). A superficial onshore earthquake that occurred in
Japan on 21 September, 2011 (JMA magnitude of 5.2, Mw = 5.1) was selected. This earth-
quake was recorded in two very close sites of the KiK-net network: the IBRH13 site (V
s30
=
335 m/s, ground type C of the EC8-1, focus distance of 10.8 km) and the IBRH14 site (V
s30
= 829 m/s, ground type A of the EC8-1, focus distance of 10.3 km). These records presented
PGA values which are close to the ones obtained in Spain after the 2011 Lorca earthquake
[109]. For this scenario, two of the adopted GMPEs use the closest distance to the rupture
[100,101]. The other two use the Joyner–Boore distance [98,99]. The comparative results
are presented in Figure 11.
Figure 11. Comparison of the response spectra obtained with several GMPEs for the near-source
scenario, the Japan earthquake records (Mw = 5.1), and the seismic actions of the Portuguese (type
2 of the NP EN 1998-1:2010 [46] for Vila Real de Santo António) and Spanish (NCSE-02 [50] for
Ayamonte) seismic codes, which are currently mandatory for each region: (a) for IBRH13 site
(ground type C) and (b) for the IBRH14 site (ground type A) [99–101].
Again, the high dispersion of the results is noticeable when observing the response
spectra obtained with different GMPEs. With this issue in mind, it is important to figure
out what are the consequences for the damage evaluation that can result from this varia-
tion observed in the estimated response spectra. In this context, two GMPEs were adopted
for each earthquake scenario, which were the ones that induced the lower and the higher
collapse ratios. Figures 12–15 show the results obtained for the scenarios that were tested
in this work for the LS of NC (a red marker with a number higher than 1.00 means that
the collapse of the school building is most likely to occur).
The damage maps obtained for the different earthquake scenarios are probably value
information. It emphasises the importance of transmitting to society that a huge amount
of uncertainty still exists in relation to the occurrence of earthquakes, with regard to their
recurrence, the propagation of seismic waves, the phenomena of local amplification or
their effects on buildings. Interestingly, the GMPE that presents the highest values for the
near-field onshore earthquake is also the one that has the lowest values for the far-field
offshore earthquake scenario. The damage that schools would effectively present due to
the earthquake scenarios that were studied would probably fall between the upper and
lower limits of the results shown in Figures 12–15, where the presented collapse ratio was
computed for the LS of NC by using Equation (2).
The enormous uncertainty inherent in seismic risk assessment procedures is ob-
served in the results obtained in this study. For this reason, it is important to transmit this
uncertainty to society and to promote a culture of risk. This is probably the only way we
can build a more resilient and sustainable society. The importance of this issue was also
very evident in Japan after the 2011 Tohoku earthquake, as has been highlighted by some
authors [110,111].
(a) (b)
Figure 11.
Comparison of the response spectra obtained with several GMPEs for the near-source
scenario, the Japan earthquake records (Mw = 5.1), and the seismic actions of the Portuguese (type 2 of
the NP EN 1998-1:2010 [
46
] for Vila Real de Santo António) and Spanish (NCSE-02 [
50
] for Ayamonte)
seismic codes, which are currently mandatory for each region: (
a
) for IBRH13 site (ground type C)
and (b) for the IBRH14 site (ground type A) [99–101].
Again, the high dispersion of the results is noticeable when observing the response
spectra obtained with different GMPEs. With this issue in mind, it is important to figure
out what are the consequences for the damage evaluation that can result from this variation
observed in the estimated response spectra. In this context, two GMPEs were adopted

Sustainability 2022,14, 15976 17 of 24
for each earthquake scenario, which were the ones that induced the lower and the higher
collapse ratios. Figures 12–15 show the results obtained for the scenarios that were tested
in this work for the LS of NC (a red marker with a number higher than 1.00 means that the
collapse of the school building is most likely to occur).
Sustainability 2022, 14, x FOR PEER REVIEW 19 of 26
Figure 12. Collapse ratios for the studied offshore earthquake scenario (M = 7.7) when using the
Idini et al. GMPE [102].
Figure 13. Collapse ratios for the studied offshore earthquake scenario (M = 7.7) when using the
Bindi et al. GMPE [100].
In the context of the Algarve and Huelva regions, it is important to remember the
destruction caused by the 1755 earthquake [89]. The Algarve was the most damaged re-
gion [112]. This is a recurrent phenomenon in this area, as there are sedimentary, palae-
ontological and geomorphological records of tsunamis of similar effects to the 1755 earth-
quake [113], as well various historical accounts of different destructive earthquakes [90].
The only way to reduce this uncertainty is to obtain records of large-magnitude earth-
quakes. These must be recorded at different distances from the source and with different
geological characteristics, which unfortunately do not exist in sufficient numbers in this
region. Even using stochastic earthquake simulation [44,107], where it is possible to con-
trol many of these factors, uncertainty is also high, and the processing speed is much lower
Figure 12.
Collapse ratios for the studied offshore earthquake scenario (M= 7.7) when using the
Idini et al. GMPE [102].
Sustainability 2022, 14, x FOR PEER REVIEW 19 of 26
Figure 12. Collapse ratios for the studied offshore earthquake scenario (M = 7.7) when using the
Idini et al. GMPE [102].
Figure 13. Collapse ratios for the studied offshore earthquake scenario (M = 7.7) when using the
Bindi et al. GMPE [100].
In the context of the Algarve and Huelva regions, it is important to remember the
destruction caused by the 1755 earthquake [89]. The Algarve was the most damaged re-
gion [112]. This is a recurrent phenomenon in this area, as there are sedimentary, palae-
ontological and geomorphological records of tsunamis of similar effects to the 1755 earth-
quake [113], as well various historical accounts of different destructive earthquakes [90].
The only way to reduce this uncertainty is to obtain records of large-magnitude earth-
quakes. These must be recorded at different distances from the source and with different
geological characteristics, which unfortunately do not exist in sufficient numbers in this
region. Even using stochastic earthquake simulation [44,107], where it is possible to con-
trol many of these factors, uncertainty is also high, and the processing speed is much lower
Figure 13.
Collapse ratios for the studied offshore earthquake scenario (M= 7.7) when using the
Bindi et al. GMPE [100].

Sustainability 2022,14, 15976 18 of 24
Sustainability 2022, 14, x FOR PEER REVIEW 20 of 26
than that resulting from the use of GMPEs, which can make their use unrealistic in soft-
ware intended for civil protection.
Figure 14. Collapse ratios for the studied near-field earthquake scenario (M = 5.2) when using the
Bindi et al. GMPE [100].
Figure 15. Collapse ratios for the studied near-field earthquake scenario (M = 5.2) when using the
Campbell and Bozorgnia GMPE [101].
The influence of uncertainty surrounding damage seems to be greater for large-mag-
nitude far-field offshore earthquake scenarios, as it influences the results of a greater num-
ber of buildings. In relation to scenarios with near-field earthquakes (with lower magni-
tudes), the differences are less significant and influence the damage results of a smaller
number of buildings.
For new buildings, the adoption of capacity design rules intends to solve the problem
of aleatory and epistemic uncertainty inherent to the effects of earthquakes on construc-
tions, such as the case of the rules presented in the EC8-1, for example. This type of struc-
tural design strategy has long been adopted as a way of desensitising the structural be-
haviour of the earthquake characteristics [114]. However, in the context of the assessment
of existing buildings, the influence of the variability of the seismic action is still an im-
portant problem that needs to be minimised. Recent seismic hazard studies have adopted
backbone approaches to capture the epistemic uncertainty, namely, by combining a set of
GMPEs within logic trees [52,115]. However, there are also issues related to this approach,
because sensitivity studies have shown that the selection of GMPEs has a greater impact
on the results than the weights assigned to each branch of the logic trees [116]. If all
branches are given an equal weight, this is equivalent to the mere arithmetic mean, which
may not be the best option, given the difference in results observed in the response spectra
presented in Figures 10 and 11. It is also not certain that these weights are equally valid
Figure 14.
Collapse ratios for the studied near-field earthquake scenario (M= 5.2) when using the
Bindi et al. GMPE [100].
Sustainability 2022, 14, x FOR PEER REVIEW 20 of 26
than that resulting from the use of GMPEs, which can make their use unrealistic in soft-
ware intended for civil protection.
Figure 14. Collapse ratios for the studied near-field earthquake scenario (M = 5.2) when using the
Bindi et al. GMPE [100].
Figure 15. Collapse ratios for the studied near-field earthquake scenario (M = 5.2) when using the
Campbell and Bozorgnia GMPE [101].
The influence of uncertainty surrounding damage seems to be greater for large-mag-
nitude far-field offshore earthquake scenarios, as it influences the results of a greater num-
ber of buildings. In relation to scenarios with near-field earthquakes (with lower magni-
tudes), the differences are less significant and influence the damage results of a smaller
number of buildings.
For new buildings, the adoption of capacity design rules intends to solve the problem
of aleatory and epistemic uncertainty inherent to the effects of earthquakes on construc-
tions, such as the case of the rules presented in the EC8-1, for example. This type of struc-
tural design strategy has long been adopted as a way of desensitising the structural be-
haviour of the earthquake characteristics [114]. However, in the context of the assessment
of existing buildings, the influence of the variability of the seismic action is still an im-
portant problem that needs to be minimised. Recent seismic hazard studies have adopted
backbone approaches to capture the epistemic uncertainty, namely, by combining a set of
GMPEs within logic trees [52,115]. However, there are also issues related to this approach,
because sensitivity studies have shown that the selection of GMPEs has a greater impact
on the results than the weights assigned to each branch of the logic trees [116]. If all
branches are given an equal weight, this is equivalent to the mere arithmetic mean, which
may not be the best option, given the difference in results observed in the response spectra
presented in Figures 10 and 11. It is also not certain that these weights are equally valid
Figure 15.
Collapse ratios for the studied near-field earthquake scenario (M= 5.2) when using the
Campbell and Bozorgnia GMPE [101].
The damage maps obtained for the different earthquake scenarios are probably value
information. It emphasises the importance of transmitting to society that a huge amount
of uncertainty still exists in relation to the occurrence of earthquakes, with regard to their
recurrence, the propagation of seismic waves, the phenomena of local amplification or
their effects on buildings. Interestingly, the GMPE that presents the highest values for the
near-field onshore earthquake is also the one that has the lowest values for the far-field
offshore earthquake scenario. The damage that schools would effectively present due to
the earthquake scenarios that were studied would probably fall between the upper and
lower limits of the results shown in Figures 12–15, where the presented collapse ratio was
computed for the LS of NC by using Equation (2).
The enormous uncertainty inherent in seismic risk assessment procedures is observed
in the results obtained in this study. For this reason, it is important to transmit this
uncertainty to society and to promote a culture of risk. This is probably the only way we
can build a more resilient and sustainable society. The importance of this issue was also
very evident in Japan after the 2011 Tohoku earthquake, as has been highlighted by some
authors [110,111].
In the context of the Algarve and Huelva regions, it is important to remember the
destruction caused by the 1755 earthquake [
89
]. The Algarve was the most damaged
region [
112
]. This is a recurrent phenomenon in this area, as there are sedimentary, palaeon-
tological and geomorphological records of tsunamis of similar effects to the 1755 earth-
quake [
113
], as well various historical accounts of different destructive earthquakes [
90
].
The only way to reduce this uncertainty is to obtain records of large-magnitude earthquakes.

Sustainability 2022,14, 15976 19 of 24
These must be recorded at different distances from the source and with different geological
characteristics, which unfortunately do not exist in sufficient numbers in this region. Even
using stochastic earthquake simulation [
44
,
107
], where it is possible to control many of
these factors, uncertainty is also high, and the processing speed is much lower than that
resulting from the use of GMPEs, which can make their use unrealistic in software intended
for civil protection.
The influence of uncertainty surrounding damage seems to be greater for large-
magnitude far-field offshore earthquake scenarios, as it influences the results of a greater
number of buildings. In relation to scenarios with near-field earthquakes (with lower
magnitudes), the differences are less significant and influence the damage results of a
smaller number of buildings.
For new buildings, the adoption of capacity design rules intends to solve the problem
of aleatory and epistemic uncertainty inherent to the effects of earthquakes on constructions,
such as the case of the rules presented in the EC8-1, for example. This type of structural
design strategy has long been adopted as a way of desensitising the structural behaviour
of the earthquake characteristics [
114
]. However, in the context of the assessment of
existing buildings, the influence of the variability of the seismic action is still an important
problem that needs to be minimised. Recent seismic hazard studies have adopted backbone
approaches to capture the epistemic uncertainty, namely, by combining a set of GMPEs
within logic trees [
52
,
115
]. However, there are also issues related to this approach, because
sensitivity studies have shown that the selection of GMPEs has a greater impact on the
results than the weights assigned to each branch of the logic trees [
116
]. If all branches
are given an equal weight, this is equivalent to the mere arithmetic mean, which may
not be the best option, given the difference in results observed in the response spectra
presented in Figures 10 and 11. It is also not certain that these weights are equally valid for
all magnitudes and distances, namely, in the context of the region under study. Moreover, it
is likely that the set of GMPEs, as well as the weights of the logic trees, should be properly
adjusted for each particular region, instead of being uniform for large areas.
In all the tested scenarios, it was the masonry school buildings that had the highest
school score in terms of possible collapse. Therefore, buildings with this structural system
are the ones where seismic retrofitting measures are most needed, which was the support
for selecting the two pilot school buildings that were retrofitted.
In relation to the differences observed between the seismic actions that are stipulated
on each side of the border between Portugal and Spain, it will be necessary to carry out
more studies. These should be of a probabilistic nature, to better define the seismic action
for the border zone between these two countries.
In this context, this type of study should be continued for this region, transcending
country borders, which is of utmost importance to increase the resilience of the communities,
as the effects of the earthquakes do not recognise international borders, which should be
reflected in the future generation of EC8.
6. Conclusions
As a result of the work carried out in the PERSISTAH project, it is possible to present
the following main conclusions:
•
It is feasible to carry out the evaluation of the seismic safety of a large number of
buildings using the analysis methods established in the EC8-3, when using dedicated
software, such as the one that was developed for the project;
•
Using this approach, it has been possible to verify the great influence of the selection
of the GMPEs on the estimation of the collapse ratio of the school buildings. Therefore,
the real degree of damage expected for the earthquake scenarios tested is not certain.
Nevertheless, it would probably be within the upper and lower limits obtained;
•
The seismic retrofitting of two pilot schools made it possible to observe the main
execution errors of the most usual solutions adopted for masonry buildings. Moreover,

Sustainability 2022,14, 15976 20 of 24
it stressed the need to provide training courses to all types of workers involved in this
type of work and not to just focus attention on structural designers;
•
The resources and educational material developed, as well as the training actions
carried out with teachers, were a great success. This shows that this procedure is one
of the best ways to create a more resilient society to the effects of earthquakes;
•
The PERSISTAH project can help government agencies to prepare a vulnerability
reduction plan, promoting structural and non-structural mitigation, to enhance the
safety of existing schools and reduce their vulnerability;
•
The fact that PERSISTAH is a cross-border project allowed a better understanding
of the differences between the seismic codes of Portugal and Spain, in particular for
school buildings. Therefore, it is desirable to carry out more joint studies concerning
the seismic hazard of these regions.
Author Contributions:
Conceptualisation and methodology, J.M.C.E., A.M.-E., L.F.S., M.A.F. and
C.S.O.; software, J.M.C.E.; validation, J.M.C.E.; formal analysis, J.M.C.E., B.T., C.E., V.B.,
M.-V.R.-G.-C.
,
E.R.-S., J.d.-M.-R. and M.-L.S.-V.; investigation, J.M.C.E., A.M.-E., M.A.F.,
M.-V.R.-G.-C.
, E.R.-S.,
J.d.-M.-R.
, M.-L.S.-V. and B.Z.B.; resources, J.M.C.E., A.C., L.F.S., A.B., M.A.F., M.-V.R.-G.-C., E.R.-S.
and
J.d.-M.-R.
; writing—original draft preparation, J.M.C.E., A.M.-E., M.-V.R.-G.-C., E.R.-S. and
B.Z.B.; writing—review and editing, J.M.C.E., A.M.-E., M.-V.R.-G.-C., M.A.F. and C.S.O.; supervision,
J.M.C.E., A.M.-E. and C.S.O.; project administration, J.M.C.E., A.M.-E. and L.F.S.; funding acquisition,
J.M.C.E., A.M.-E., L.F.S., M.A.F. and C.S.O. All authors have read and agreed to the published version
of the manuscript.
Funding:
This research was funded by the INTERREG-POCTEP España–Portugal programme and
the European Regional Development Fund through the 0313_PERSISTAH_5_P project.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement:
All detailed information about the PERSISTAH project can be found at
the following link: https://sites.google.com/view/persistah/en, accessed on 30 October 2022.
Acknowledgments:
The authors wish to thank the Municipalities of the Algarve that have con-
tributed to this project, in particular the Municipality of Olhão, the General Directorate for Schools
(Algarve Region Service Directorate of Faro), and the Portuguese General Secretariat of the Min-
istry of Education and Science of Lisbon, for providing information and architectural drawings of
some school buildings. The first author would also like to acknowledge the financial support of the
Portuguese Foundation of Science and Technology (FCT) of CIMA through UIDP/00350/2020.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design
of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or
in the decision to publish the results.
References
1.
UN. The 17 Sustainable Development Goals (SDGs). United Nations. Available online: https://sdgs.un.org/goals (accessed on
20 December 2021).
2.
Mendonça, D.; Amorim, I.; Kagohara, M. An historical perspective on community resilience: The case of the 1755 Lisbon
Earthquake. Int. J. Disaster Risk Reduct. 2019,34, 363–374. [CrossRef]
3.
Winstanley, A.; Hepi, M.; Wood, D. Resilience? Contested meanings and experiences in post-disaster Christchurch, New Zealand.
K¯
otuitui N. Z. J. Soc. Sci. Online 2015,10, 126–134. [CrossRef]
4.
Xi, Y.; Yu, H.; Yao, Y.; Peng, K.; Wang, Y.; Chen, R. Post-traumatic stress disorder and the role of resilience, social support, anxiety
and depression after the Jiuzhaigou earthquake: A structural equation model. Asian J. Psychiatry
2020
,49, 101958. [CrossRef]
[PubMed]
5.
Bal, ˙
I.E.; Smyrou, E. Simulation of the earthquake-induced collapse of a school building in Turkey in 2011 Van Earthquake. Bull.
Earthq. Eng. 2016,14, 3509–3528. [CrossRef]
6.
Chen, H.; Xie, Q.; Lan, R.; Li, Z.; Xu, C.; Yu, S. Seismic damage to schools subjected to Nepal earthquakes, 2015. Nat. Hazards
2017
,
88, 247–284. [CrossRef]
7.
Di Ludovico, M.; Digrisolo, A.; Moroni, C.; Graziotti, F.; Manfredi, V.; Prota, A.; Dolce, M.; Manfredi, G. Remarks on damage and
response of school buildings after the Central Italy earthquake sequence. Bull. Earthq. Eng. 2019,17, 5679–5700. [CrossRef]

Sustainability 2022,14, 15976 21 of 24
8.
Kabeyasawa, T. Damages to RC school buildings and lessons from the 2011 East Japan earthquake. Bull. Earthq. Eng.
2017
,15,
535–553. [CrossRef]
9.
Oyguc, R. Seismic performance of RC school buildings after 2011 Van earthquakes. Bull. Earthq. Eng.
2016
,14, 821–847. [CrossRef]
10.
Angelier, J.; Lee, J.-C.; Hu, J.-C.; Chu, H.-T. Three-dimensional deformation along the rupture trace of the September 21st, 1999,
Taiwan earthquake: A case study in the Kuangfu school. J. Struct. Geol. 2003,25, 351–370. [CrossRef]
11.
Global_Education_Cluster. Disaster Risk Reduction in Education in Emergencies—A Guidance Note for Education Clusters and
Sector Coordination Groups. Available online: https://reliefweb.int/attachments/596e560e-cf6c-3a3c-ab27-576212068dbc/Full_
report.pdf (accessed on 5 November 2021).
12.
Calvi, G.M.; Pinho, R.; Magenes, G.; Bommer, J.J.; Restrepo-Vélez, L.F.; Crowley, H. Development of seismic vulnerability
assessment methodologies over the past 30 years. ISET J. Earthq. Technol. 2006,43, 75–104.
13.
Maio, R.; Estêvão, J.M.C.; Ferreira, T.M.; Vicente, R. Casting a new light on the seismic risk assessment of stone masonry buildings
located within historic centres. Structures 2020,25, 578–592. [CrossRef]
14.
Candeias, P.; Vicente, M.; Rupakhety, R.; Lopes, M.; Ferreira, M.A.; Oliveira, C.S. Seismic Performance of Non-structural Elements
Assessed Through Shake Table Tests: The KnowRISK Room Set-Up. In Proceedings of the International Conference on Earthquake
Engineering and Structural Dynamics, Cham, Iceland, 12–14 June 2017; pp. 293–307. [CrossRef]
15.
Mutch, C. The role of schools in disaster preparedness, response and recovery: What can we learn from the literature? Pastor. Care
Educ. 2014,32, 5–22. [CrossRef]
16.
Mutch, C. Leadership in times of crisis: Dispositional, relational and contextual factors influencing school principals’ actions.
Int. J. Disaster Risk Reduct. 2015,14, 186–194. [CrossRef]
17.
Notman, R. Seismic Leadership, Hope, and Resiliency: Stories of Two Christchurch Schools Post-Earthquake. Leadersh. Policy Sch.
2015,14, 437–459. [CrossRef]
18.
Tan, K.T.; Abdul Razak, H.; Lu, D.; Li, Y. Seismic response of a four-storey RC school building with masonry-infilled walls.
Nat. Hazards 2015,78, 141–153. [CrossRef]
19. El-Betar, S.A. Seismic vulnerability evaluation of existing R.C. buildings. HBRC J. 2018,14, 189–197. [CrossRef]
20.
Korkmaz, M.; Ozdemir, M.A.; Kavali, E.; Cakir, F. Performance-based assessment of multi-story unreinforced masonry buildings:
The case of historical Khatib School in Erzurum, Turkey. Eng. Fail. Anal. 2018,94, 195–213. [CrossRef]
21.
O’Reilly, G.J.; Perrone, D.; Fox, M.; Monteiro, R.; Filiatrault, A. Seismic assessment and loss estimation of existing school buildings
in Italy. Eng. Struct. 2018,168, 142–162. [CrossRef]
22.
Perrone, D.; O’Reilly, G.J.; Monteiro, R.; Filiatrault, A. Assessing seismic risk in typical Italian school buildings: From in-situ
survey to loss estimation. Int. J. Disaster Risk Reduct. 2020,44, 101448. [CrossRef]
23.
Pan, H.; Kusunoki, K. Aftershock damage prediction of reinforced-concrete buildings using capacity spectrum assessments.
Soil Dyn. Earthq. Eng. 2020,129, 105952. [CrossRef]
24.
Clementi, F.; Gazzani, V.; Poiani, M.; Lenci, S. Assessment of seismic behaviour of heritage masonry buildings using numerical
modelling. J. Build. Eng. 2016,8, 29–47. [CrossRef]
25.
Hancilar, U.; Çaktı, E.; Erdik, M.; Franco, G.E.; Deodatis, G. Earthquake vulnerability of school buildings: Probabilistic structural
fragility analyses. Soil Dyn. Earthq. Eng. 2014,67, 169–178. [CrossRef]
26.
Tang, B.; Lu, X.; Ye, L.; Shi, W. Evaluation of collapse resistance of RC frame structures for Chinese schools in seismic design
categories B and C. Earthq. Eng. Eng. Vib. 2011,10, 369. [CrossRef]
27.
Hadzima-Nyarko, M.; Ademovi´c, N.; Krajnovi´c, M. Architectural characteristics and determination of load-bearing capacity as a
key indicator for a strengthening of the primary school buildings: Case study Osijek. Structures 2021,34, 3996–4011. [CrossRef]
28.
Karapetrou, S.; Manakou, M.; Bindi, D.; Petrovic, B.; Pitilakis, K. “Time-building specific” seismic vulnerability assessment of a
hospital RC building using field monitoring data. Eng. Struct. 2016,112, 114–132. [CrossRef]
29.
Trevlopoulos, K.; Guéguen, P. Period elongation-based framework for operative assessment of the variation of seismic vulnerabil-
ity of reinforced concrete buildings during aftershock sequences. Soil Dyn. Earthq. Eng. 2016,84, 224–237. [CrossRef]
30.
Shamsoddini Motlagh, Z.; Raissi Dehkordi, M.; Eghbali, M.; Samadian, D. Evaluation of seismic resilience index for typical RC
school buildings considering carbonate corrosion effects. Int. J. Disaster Risk Reduct. 2020,46, 101511. [CrossRef]
31.
Chrysostomou, C.Z.; Kyriakides, N.; Papanikolaou, V.K.; Kappos, A.J.; Dimitrakopoulos, E.G.; Giouvanidis, A.I. Vulnerability
assessment and feasibility analysis of seismic strengthening of school buildings. Bull. Earthq. Eng.
2015
,13, 3809–3840. [CrossRef]
32.
Samadian, D.; Ghafory-Ashtiany, M.; Naderpour, H.; Eghbali, M. Seismic resilience evaluation based on vulnerability curves for
existing and retrofitted typical RC school buildings. Soil Dyn. Earthq. Eng. 2019,127, 105844. [CrossRef]
33.
Sobaih, M.E.; Nazif, M.A. A proposed methodology for seismic risk evaluation of existing reinforced school buildings. HBRC J.
2012,8, 204–211. [CrossRef]
34.
Figueroa, E.A.P.; Malisan, P.; Grimaz, S. Implementation of seismic assessment of schools in El Salvador. Int. J. Disaster Risk
Reduct. 2020,45, 101449. [CrossRef]
35. Grimaz, S.; Malisan, P. Multi-hazard visual inspection for defining safety upgrading strategies of learning facilities at territorial
level: VISUS methodology. Int. J. Disaster Risk Reduct. 2020,44, 101435. [CrossRef]
36.
Chen, C.-S.; Cheng, M.-Y.; Wu, Y.-W. Seismic assessment of school buildings in Taiwan using the evolutionary support vector
machine inference system. Expert Syst. Appl. 2012,39, 4102–4110. [CrossRef]

Sustainability 2022,14, 15976 22 of 24
37. Chen, H.-M.; Kao, W.-K.; Tsai, H.-C. Genetic programming for predicting aseismic abilities of school buildings. Eng. Appl. Artif.
Intell. 2012,25, 1103–1113. [CrossRef]
38.
Kao, W.-K.; Chen, H.-M.; Chou, J.-S. Aseismic ability estimation of school building using predictive data mining models. Expert
Syst. Appl. 2011,38, 10252–10263. [CrossRef]
39.
Chuang, M.-C.; Liao, E.; Lai, V.P.; Yu, Y.-J.; Tsai, K.-C. Development of PISA4SB for Applications in the Taiwan School Building
Seismic Retrofit Program. Procedia Eng. 2011,14, 965–973. [CrossRef]
40.
D’Ayala, D.; Galasso, C.; Nassirpour, A.; Adhikari, R.K.; Yamin, L.; Fernandez, R.; Lo, D.; Garciano, L.; Oreta, A. Resilient
communities through safer schools. Int. J. Disaster Risk Reduct. 2020,45, 101446. [CrossRef]
41.
UN. International Strategy for Disaster Reduction Hyogo Framework for Action 2005–2015: Building the Resilience of Nations, 1st ed.;
United Nations: Geneva, Switzerland, 2007.
42.
UN. Sendai Framework for Disaster Risk Reduction 2015–2030. Third UN World Conference on Disaster Risk Reduction, 1st ed.; United
Nations: Geneva, Switzerland, 2015.
43.
Estêvão, J.M.C. An integrated computational approach for seismic risk assessment of individual buildings. Appl. Sci.
2019
,9,
5088. [CrossRef]
44.
Estêvão, J.M.C.; Oliveira, C.S. Point and fault rupture stochastic methods for generating simulated accelerograms considering soil
effects for structural analysis. Soil Dyn. Earthq. Eng. 2012,43, 329–341. [CrossRef]
45.
CEN. EN 1998-1:2004; Eurocode 8, Design of Structures for Earthquake Resistance—Part 1: General Rules, Seismic Actions and
Rules for Buildings. ComitéEuropéen de Normalisation: Bruxelles, Belgique, 2004; p. 229.
46.
IPQ. NP EN 1998-1; Eurocódigo 8: Projecto de Estruturas Para Resistência aos Sismos. Parte 1: Regras Gerais, Acções Sísmicas e
Regras Para Edifícios (in Portuguese). Instituto Português da Qualidade: Caparica, Portugal, 2010; p. 230.
47.
Estêvão, J.M.C.; Tomás, B. Ranking the Seismic Vulnerability of Masonry School Buildings according to the EC8-3 by Using
Performance Curves. Int. J. Archit. Herit. 2022,16, 1699–1714. [CrossRef]
48.
Estêvão, J.M.C.; Esteves, C. Nonlinear Seismic Analysis of Existing RC School Buildings: The “P3” School Typology. Buildings
2020,10, 210. [CrossRef]
49.
Esteban, A.M.; Sánchez, E.R.; Blanco, B.Z.; Cruz, M.V.R.G.d.l.; Rodríguez, J.d.M.; Estêvão, J. Schools, Seismicity and Retrofitting;
Editorial Universidad de Sevilla: Seville, Spain, 2021; p. 164. [CrossRef]
50.
NCSE-02; Norma de Construcción Sismorresistente: Parte General y Edificación. Real Decreto 997/2002 (in Spanish). Ministerio
de Fomento de España: Madrid, Spain, 2002.
51.
Woessner, J.; Laurentiu, D.; Giardini, D.; Crowley, H.; Cotton, F.; Grünthal, G.; Valensise, G.; Arvidsson, R.; Basili, R.; Demircioglu,
M.B.; et al. The 2013 European Seismic Hazard Model: Key components and results. Bull. Earthq. Eng.
2015
,13, 3553–3596.
[CrossRef]
52.
Weatherill, G.; Kotha, S.R.; Cotton, F. A regionally-adaptable “scaled backbone” ground motion logic tree for shallow seismicity
in Europe: Application to the 2020 European seismic hazard model. Bull. Earthq. Eng. 2020,18, 5087–5117. [CrossRef]
53.
IPQ. NP EN 1998-5; Eurocódigo 8: Projecto de Estruturas Para Resistência aos Sismos. Parte 5: Fundações, Estruturas de Suporte
e Aspectos Geotécnicos (in Portuguese). Instituto Português da Qualidade: Caparica, Portugal, 2010; p. 54.
54.
Sousa, M.L.; Campos Costa, A. Ground motion scenarios consistent with probabilistic seismic hazard disaggregation analysis.
Application to Mainland Portugal. Bull. Earthq. Eng. 2009,7, 127–147. [CrossRef]
55.
Gràcia, E.; Dañobeitia, J.; Vergés, J.; Bartolomé, R.; Córdoba, D. Crustal architecture and tectonic evolution of the Gulf of Cadiz
(SW Iberian margin) at the convergence of the Eurasian and African plates. Tectonics 2003,22, 1033. [CrossRef]
56.
Custódio, S.; Dias, N.A.; Carrilho, F.; Góngora, E.; Rio, I.; Marreiros, C.; Morais, I.; Alves, P.; Matias, L. Earthquakes in western
Iberia: Improving the understanding of lithospheric deformation in a slowly deforming region. Geophys. J. Int.
2015
,203, 127–145.
[CrossRef]
57. IGN. Instituto Geográfico Nacional. Available online: https://www.ign.es (accessed on 25 November 2021).
58.
Custódio, S.; Lima, V.; Vales, D.; Cesca, S.; Carrilho, F. Imaging active faulting in a region of distributed deformation from the
joint clustering of focal mechanisms and hypocentres: Application to the Azores–western Mediterranean region. Tectonophysics
2016,676, 70–89. [CrossRef]
59.
Wells, D.L.; Coppersmith, K.J. New empirical relationships among magnitude, rupture length, rupture width, rupture area, and
surface displacement. Bull. Seismol. Soc. Am. 1994,84, 974–1002.
60.
CEN. EN 1998-3: 2005; Eurocode 8, Design of Structures for Earthquake Resistance—Part 3: Assessment and Retrofitting of
Buildings. ComitéEuropéen de Normalisation: Brussels, Belgique, 2005; p. 89.
61.
IPQ. NP EN 1998-3; Eurocódigo 8: Projecto de Estruturas Para Resistência aos Sismos. Parte 3: Avaliação e Reabilitação de
Edifícios (in Portuguese). Instituto Português da Qualidade: Caparica, Portugal, 2017; p. 230.
62.
Lagomarsino, S.; Penna, A.; Galasco, A.; Cattari, S. TREMURI program: An equivalent frame model for the nonlinear seismic
analysis of masonry buildings. Eng. Struct. 2013,56, 1787–1799. [CrossRef]
63.
Barreto, V.; Estêvão, J.M.C. Feasibility of Using Steel Bracings for Seismic Retrofitting of RC School Buildings. In Proceedings of the
INCREaSE 2019; Springer: Cham, Switzerland, 2019; pp. 1117–1127. [CrossRef]
64.
Seismosoft. SeismoStruct 2016 Release-1—A Computer Program for Static and Dynamic Nonlinear Analysis of Framed Structures.
2016. Available online: http://www.seismosoft.com (accessed on 29 July 2017).

Sustainability 2022,14, 15976 23 of 24
65.
Estêvão, J.M.C. Feasibility of using neural networks to obtain simplified capacity curves for seismic assessment. Buildings
2018
,8,
151. [CrossRef]
66.
IGN. Actualización de Mapas de Peligrosidad Sísmica de España 2012 (in Spanish); Centro Nacional de Información Geográfica (CNIG):
Madrid, Spain, 2017. [CrossRef]
67.
Segovia-Verjel, M.-L.; Requena-García-Cruz, M.-V.; de-Justo-Moscardó, E.; Morales-Esteban, A. Optimal seismic retrofitting
techniques for URM school buildings located in the southwestern Iberian peninsula. PLoS ONE
2019
,14, e0223491. [CrossRef]
[PubMed]
68.
McKenna, F.; Scott Michael, H.; Fenves Gregory, L. Nonlinear Finite-Element Analysis Software Architecture Using Object
Composition. J. Comput. Civ. Eng. 2010,24, 95–107. [CrossRef]
69.
Couto, R.; Requena-García-Cruz, M.V.; Bento, R.; Morales-Esteban, A. Seismic capacity and vulnerability assessment considering
ageing effects: Case study—Three local Portuguese RC buildings. Bull. Earthq. Eng. 2021,19, 6591–6614. [CrossRef]
70.
Requena-Garcia-Cruz, M.V.; Romero-Sánchez, E.; Morales-Esteban, A. Numerical investigation of the contribution of the soil-
structure interaction effects to the seismic performance and the losses of RC buildings. Dev. Built Environ.
2022
,12, 100096.
[CrossRef]
71.
Dolce, M.; Speranza, E.; De Martino, G.; Conte, C.; Giordano, F. The implementation of the Italian National Seismic Prevention
Plan: A focus on the seismic upgrading of critical buildings. Int. J. Disaster Risk Reduct. 2021,62, 102391. [CrossRef]
72.
Grant, D.N.; Bommer, J.J.; Pinho, R.; Calvi, G.M.; Goretti, A.; Meroni, F. A Prioritization Scheme for Seismic Intervention in School
Buildings in Italy. Earthq. Spectra 2007,23, 291–314. [CrossRef]
73.
Ferreira, M. Risco Sísmico em Sistemas Urbanos (in Portuguese). Ph.D. Thesis, Instituto Superior Técnico, Lisboa, Portugal, 2012.
74.
Chung, L.-L.; Yang, Y.-S.; Lien, K.-H.; Wu, L.-Y. In situ experiment on retrofit of school buildings by adding sandwich columns to
partition brick walls. Earthq. Eng. Struct. Dyn. 2014,43, 339–355. [CrossRef]
75.
Formisano, A.; Iaquinandi, A.; Mazzolani, F.M. Seismic Retrofitting by FRP of a School Building Damaged by Emilia-Romagna
Earthquake. Key Eng. Mater. 2014,624, 106–113. [CrossRef]
76.
Huang, C.H.; Chang, W.; Liu, S.H. Seismic Retrofit of a Typical School Building Using Column Jacketing and Supplement Beams.
Appl. Mech. Mater. 2014,501–504, 1556–1559. [CrossRef]
77.
Kaltakci, M.Y.; Arslan, M.H.; Yilmaz, U.S.; Arslan, H.D. A new approach on the strengthening of primary school buildings in
Turkey: An application of external shear wall. Build. Environ. 2008,43, 983–990. [CrossRef]
78.
Naja, M.K.; Baytiyeh, H. Towards safer public school buildings in Lebanon: An advocacy for seismic retrofitting initiative. Int. J.
Disaster Risk Reduct. 2014,8, 158–165. [CrossRef]
79. Nakano, Y. Seismic rehabilitation of school buildings in Japan. J. Jpn. Assoc. Earthq. Eng. 2004,4, 218–229. [CrossRef]
80.
Seo, H.; Kim, J.; Kwon, M. Optimal seismic retrofitted RC column distribution for an existing school building. Eng. Struct.
2018
,
168, 399–404. [CrossRef]
81.
Sorace, S.; Terenzi, G. Motion control-based seismic retrofit solutions for a R/C school building designed with earlier Technical
Standards. Bull. Earthq. Eng. 2014,12, 2723–2744. [CrossRef]
82.
The World Bank. Making Schools Resilient at Scale: The Case of Japan; Bogaerts, V.R., Kaneda, K.S., Eds.; The Word Bank: Washington,
DC, USA, 2016; p. 94.
83.
Estêvão, J.; Tomás, B.; Laranja, R.; Braga, A. Seismic Retrofitting of an Existing Masonry School Building: A Case Study in
Algarve. In Sustainability and Automation in Smart Constructions; Rodrigues, H., Gaspar, F., Fernandes, P., Mateus, A., Eds.; Springer
International Publishing: Cham, Switzerland, 2021; pp. 349–355.
84.
Lew, M.; Naeim, F.; Carpenter, L.D.; Youssef, N.F.; Rojas, F.; Saragoni, G.R.; Adaros, M.S. The significance of the 27 February 2010
offshore Maule, Chile earthquake. Struct. Des. Tall Spec. Build. 2010,19, 826–837. [CrossRef]
85.
Sakurai, A.; Sato, T.; Murayama, Y. Impact evaluation of a school-based disaster education program in a city affected by the 2011
great East Japan earthquake and tsunami disaster. Int. J. Disaster Risk Reduct. 2020,47, 101632. [CrossRef]
86. Ferreira, M.A.; Oliveira, C.S.; Estêvão, J.; Esteban, A.M.; Blanco, B.Z.; Sánchez, E.R.; Rodríguez, J.d.M.; Cruz, M.V.R.G.d.l.; Sá, L.
Why Does the Ground Shake? Editorial Universidad de Sevilla: Seville, Spain, 2020; p. 88. [CrossRef]
87. Ferreira, M.A.; Oliveira, C.S.; Estêvão, J.; Esteban, A.M.; Blanco, B.Z.; Sánchez, E.R.; Rodríguez, J.d.M.; Cruz, M.V.R.G.d.l.; Sá, L.
Practical Guide for Earthquake Resilient Schools; Editorial Universidad de Sevilla: Seville, Spain, 2020; p. 50. [CrossRef]
88.
#ESTUDOEMCASA. Ciências Naturais e Cidadania—7.
◦
e 8.
◦
anos. Atividade sísmica | Aula 23 | 27 min | 23 Abr. 2021.
Available online: https://www.rtp.pt/play/estudoemcasa/p7834/e539122/ciencias-naturais-e- cidadania-7- e-8- anos (accessed
on 20 December 2021).
89.
Chester, D.K.; Chester, O.K. The impact of eighteenth century earthquakes on the Algarve region, southern Portugal. Geogr. J.
2010,176, 350–370. [CrossRef]
90.
Udías, A. Large Earthquakes and Tsunamis at Saint Vincent Cape before the Lisbon 1755 Earthquake: A Historical Review. Pure
Appl. Geophys. 2020,177, 1739–1745. [CrossRef]
91.
Pro, C.; Buforn, E.; Udías, A.; Borges, J.; Oliveira, C.S. Study of the PGV, Strong Motion and Intensity Distribution of the February
1969 (Ms 8.0) Offshore Cape St. Vincent (Portugal) Earthquake Using Synthetic Ground Velocities. Pure Appl. Geophys.
2020
,177,
1809–1829. [CrossRef]
92.
Douglas, J.; Edwards, B. Recent and future developments in earthquake ground motion estimation. Earth-Sci. Rev.
2016
,160,
203–219. [CrossRef]

Sustainability 2022,14, 15976 24 of 24
93.
Kaklamanos, J.; Baise, L.G.; Boore, D.M. Estimating Unknown Input Parameters when Implementing the NGA Ground-Motion
Prediction Equations in Engineering Practice. Earthq. Spectra 2011,27, 1219–1235. [CrossRef]
94.
CESMD. Center for Engineering Strong Motion Data. Available online: https://www.strongmotioncenter.org/ (accessed on
5 November 2021).
95.
Kaiser, A.; Houtte, C.V.; Perrin, N.; McVerry, G.; Cousins, J.; Dellow, S. Characterizing GeoNet strong motion sites: Site metadata
update for the 2015 Strong Motion Database. In Proceedings of the NZSEE Conference 2016, Christchurch, New Zealand,
1–3 April 2016; pp. 1–8.
96.
Whitney, R. Ground motion processing and observations for the near-field accelerograms from the 2015 Gorkha, Nepal earthquake.
Soil Dyn. Earthq. Eng. 2018,107, 250–263. [CrossRef]
97.
Kaklamanos, J.; Baise, L.G. Model Validations and Comparisons of the Next Generation Attenuation of Ground Motions
(NGA–West) Project. Bull. Seismol. Soc. Am. 2011,101, 160–175. [CrossRef]
98.
Akkar, S.; Sandıkkaya, M.A.; Bommer, J.J. Empirical ground-motion models for point- and extended-source crustal earthquake
scenarios in Europe and the Middle East. Bull. Earthq. Eng. 2014,12, 359–387. [CrossRef]
99.
Ambraseys, N.N.; Douglas, J.; Sarma, S.K.; Smit, P.M. Equations for the Estimation of Strong Ground Motions from Shallow Crustal
Earthquakes Using Data from Europe and the Middle East: Horizontal Peak Ground Acceleration and Spectral Acceleration.
Bull. Earthq. Eng. 2005,3, 1–53. [CrossRef]
100.
Bindi, D.; Cotton, F.; Kotha, S.R.; Bosse, C.; Stromeyer, D.; Grünthal, G. Application-driven ground motion prediction equation for
seismic hazard assessments in non-cratonic moderate-seismicity areas. J. Seismol. 2017,21, 1201–1218. [CrossRef]
101.
Campbell, K.W.; Bozorgnia, Y. NGA-West2 Ground Motion Model for the Average Horizontal Components of PGA, PGV, and 5%
Damped Linear Acceleration Response Spectra. Earthq. Spectra 2014,30, 1087–1115. [CrossRef]
102.
Idini, B.; Rojas, F.; Ruiz, S.; Pastén, C. Ground motion prediction equations for the Chilean subduction zone. Bull. Earthq. Eng.
2017,15, 1853–1880. [CrossRef]
103.
Phung, V.-B.; Loh, C.H.; Chao, S.H.; Abrahamson, N.A. Ground motion prediction equation for Taiwan subduction zone
earthquakes. Earthq. Spectra 2020,36, 1331–1358. [CrossRef]
104.
NIED. National Research Institute for Earth Science and Disaster Resilience. Available online: https://www.kyoshin.bosai.go.jp/
(accessed on 5 November 2021).
105.
Hirose, F.; Miyaoka, K.; Hayashimoto, N.; Yamazaki, T.; Nakamura, M. Outline of the 2011 off the Pacific coast of Tohoku
Earthquake (Mw 9.0)—Seismicity: Foreshocks, mainshock, aftershocks, and induced activity. Earth Planets Space
2011
,63, 1.
[CrossRef]
106.
Ammon, C.J.; Lay, T.; Kanamori, H.; Cleveland, M. A rupture model of the 2011 off the Pacific coast of Tohoku Earthquake. Earth
Planets Space 2011,63, 33. [CrossRef]
107.
Estêvão, J.M.C.; Carvalho, A. The role of source and site effects on structural failures due to Azores earthquakes. Eng. Fail. Anal.
2015,56, 429–440. [CrossRef]
108.
Bulian, F.; Sierro, F.J.; Ledesma, S.; Jiménez-Espejo, F.J.; Bassetti, M.-A. Messinian West Alboran Sea record in the proximity of
Gibraltar: Early signs of Atlantic-Mediterranean gateway restriction. Mar. Geol. 2021,434, 106430. [CrossRef]
109.
Cabañas, L.; Alcalde, J.M.; Carreño, E.; Bravo, J.B. Characteristics of observed strong motion accelerograms from the 2011 Lorca
(Spain) Earthquake. Bull. Earthq. Eng. 2014,12, 1909–1932. [CrossRef]
110. Geller, R.J. Shake-up time for Japanese seismology. Nature 2011,472, 407–409. [CrossRef]
111.
Stein, S.; Geller, R.J.; Liu, M. Why earthquake hazard maps often fail and what to do about it. Tectonophysics
2012
,562–563, 1–25.
[CrossRef]
112.
Teves-Costa, P.; Batlló, J.; Matias, L.; Catita, C.; Jiménez, M.J.; García-Fernández, M. Maximum intensity maps (MIM) for Portugal
mainland. J. Seismol. 2019,23, 417–440. [CrossRef]
113.
Lario, J.; Zazo, C.; Goy, J.L.; Silva, P.G.; Bardaji, T.; Cabero, A.; Dabrio, C.J. Holocene palaeotsunami catalogue of SW Iberia.
Quat. Int. 2011,242, 196–200. [CrossRef]
114.
Paulay, T.; Priestley, M.J.N. Seismic Design of Reinforced Concrete and Masonry Buildings; John Wiley & Sons, Inc: Hoboken, NJ, USA,
1992.
115.
Kowsari, M.; Ghasemi, S. A backbone probabilistic seismic hazard analysis for the North Tehran Fault scenario. Soil Dyn. Earthq.
Eng. 2021,144, 106672. [CrossRef]
116.
Sabetta, F.; Lucantoni, A.; Bungum, H.; Bommer, J.J. Sensitivity of PSHA results to ground motion prediction relations and
logic-tree weights. Soil Dyn. Earthq. 2005,25, 317–329. [CrossRef]