Study of the Effect of the Strategy of Heating on the Mudejar Church of Santa Maria in Ateca (Spain) for Preventive Conservation of the Altarpiece Surroundings

The mudejar church of Santa Maria (Ateca) is valuable for its architecture and the altarpiece contained inside. Ateca is a village with continental climate characterized by cold winters and hot summers. In this paper we are interested in analysing the effect of temperature and relative humidity (RH) changes produced by the heating system on the altarpiece. Therefore, a monitoring system of 15 temperature and 15 relative humidity sensors was installed with a recording frequency of a data point per minute. The main contribution of this paper is the quantitative study of the effect of the heating system on the thermo-hygrometric parameters using statistical techniques such as ANOVA, mean daily trajectories or bivariate plots, and the proposal of an innovative dynamic contour plot. As results, the heating system produces a substantial increase (decrease) of temperature (RH) causing an hourly variation of these physical parameters detrimental to the conservation of the altarpiece, especially in its higher areas.This work was partially supported by the Spanish Government (Ministerio de Ciencia e Innovacion) under projects HAR2010-21944-C02-01 and HAR2010-21944-C02-02. The authors thank the companies Albarium S.L., that made the restoration, and Artechnology S.L., which supplied the sensors and to Carmen Perez from Instituto Valenciano de Conservacion y Restauracion de Bienes Culturales (IVC+R).García Diego, FJ.; Fernández Navajas, A.; Beltrán Medina, P.; Merello Giménez, P. (2013). Study of the Effect of the Strategy of Heating on the Mudejar Church of Santa Maria in Ateca (Spain) for Preventive Conservation of the Altarpiece Surroundings. Sensors. 13(9):11407-11423. https://doi.org/10.3390/s130911407S114071142313

Characterisation of thermo-hygrometric conditions of an archaeological site affected by unlike boundary weather conditions

This paper applies statistical techniques to analyse microclimatic data (temperature and relative humidity) recorded at the archaeological site of Plaza de l'Almoina (Valencia, Spain). This study has allowed us to quantify the effect of certain measures that were adopted for preventive conservation. The first monitoring campaign took place in 2010 at this archaeological site, showing harmful effects on the conservation state of the remains due to the presence of a skylight that partly covers the remains and causes a greenhouse effect. This skylight was covered with a water layer to prevent overheating of this archaeological site. However, this layer was removed in 2013 due to water leaks, and the indoor conditions changed. Over the summer, a temporary canvas was installed over the skylight to avoid heating of the archaeological site below by preventing the incidence of direct sunlight. The main importance of this work was to characterise the effect of unlike boundary weather conditions of different years in the indoor microclimate of the archaeological site, and to study the effect of the new boundary situation. This paper shows that the removal of water from the skylight caused a temperature increase inside the museum; meanwhile, the subsequent installation of the canvas cover allows appropriate daily cycles of temperature and relative humidity, especially in areas under the skylight. This work also shows that the replacement of a water ditch near the archaeological site by a PVC pipe was also detected by the sensors due to the difference in water vapour pressure.This work was partially supported by the Spanish Government (Ministerio de Ciencia e Innovacion) with grants numbers HAR2010-21944-C02-01 and HAR2010-21944-C02-02. The authors thank the personal collaboration of the archaeologist Albert Ribera and Carmen Perez.Merello Gimenez, P.; Fernández Navajas, A.; Curiel Esparza, J.; Zarzo Castelló, M.; García Diego, FJ. (2014). Characterisation of thermo-hygrometric conditions of an archaeological site affected by unlike boundary weather conditions. Building and Environment. 76:125-133. doi:10.1016/j.buildenv.2014.03.009S1251337

Sensors and Technologies in Spain: State-of-the-Art

The aim of this special issue was to provide a comprehensive view on the state-of-the-art sensor technology in Spain. Different problems cause the appearance and development of new sensor technologies and vice versa, the emergence of new sensors facilitates the solution of existing real problems. [...

Statistical tools applied in the characterisation and evaluation of a thermo-hygrometric corrective action carried out at the noheda archaeological site (Noheda, Spain)

The Noheda archaeological site is unique and exceptional for its size, and the quality and conservation condition of the Roman mosaic pavement covering its urban pars. In 2008 a tent was installed as protection from rain and sun. Being of interest to characterise the microclimate of the remains, six probes with relative humidity and temperature sensors were installed in 2013 for this purpose. Microclimate monitoring allowed us to check relative humidity differences resulting from the groundwater level, as well as inner sensors reaching maximum temperatures higher than the outdoors ones as a consequence of the non-ventilated tent covering the archaeological site. Microclimatic conditions in the archaeological site were deemed detrimental for the conservation of the mosaics. Thus, in summer 2013, expanded clay and geotextile were installed over the mosaics as a corrective action. The outcomes of this study have proven the effectiveness of this solution to control temperature and relative humidity, helping to configure a more stable microclimate suitable for preservation of the mosaic.Our thanks to the Directorate General of Cultural Heritage of the Council of Education, Culture and Sport in the Community Council of Castilla-La Mancha, and to the Provincial Deputation of Cuenca for the institutional and economical support that they have been giving us throughout these years, which has been vital for the maintenance and adequate progress of the research project that offers relevant scientific results. This work was partially supported by the Spanish Government (Ministerio de Ciencia e Innovacion) under projects HAR2010-21944-C02-01 and HAR2010-21944-C02-02.Valero, MÁ.; Merello Gimenez, P.; Fernández Navajas, A.; García Diego, FJ. (2014). Statistical tools applied in the characterisation and evaluation of a thermo-hygrometric corrective action carried out at the noheda archaeological site (Noheda, Spain). Sensors. 14(1):1665-1679. doi:10.3390/s140101665S16651679141Valero Tévar, M. Á. (2013). The late-antique villa at Noheda (Villar de Domingo García) near Cuenca and its mosaics. Journal of Roman Archaeology, 26, 307-330. doi:10.1017/s1047759413000172Nava, S., Becherini, F., Bernardi, A., Bonazza, A., Chiari, M., García-Orellana, I., … Vecchi, R. (2010). An integrated approach to assess air pollution threats to cultural heritage in a semi-confined environment: The case study of Michelozzo’s Courtyard in Florence (Italy). Science of The Total Environment, 408(6), 1403-1413. doi:10.1016/j.scitotenv.2009.07.030Kisternaya, M., & Kozlov, V. (2012). Preservation of historic monuments in the «Kizhi» Open-Air Museum (Russian Federation). Journal of Cultural Heritage, 13(3), S74-S78. doi:10.1016/j.culher.2012.03.013Calia, A., Lettieri, M., Leucci, G., Matera, L., Persico, R., & Sileo, M. (2013). The mosaic of the crypt of St. Nicholas in Bari (Italy): integrated GPR and laboratory diagnostic study. Journal of Archaeological Science, 40(12), 4162-4169. doi:10.1016/j.jas.2013.06.005Moropoulou, A., Bakolas, A., Karoglou, M., Delegou, E. T., Labropoulos, K. C., & Katsiotis, N. S. (2013). Diagnostics and protection of Hagia Sophia mosaics. Journal of Cultural Heritage, 14(3), e133-e139. doi:10.1016/j.culher.2013.01.006Alberghina, M. F., Barraco, R., Basile, S., Brai, M., Pellegrino, L., Prestileo, F., … Tranchina, L. (2014). Mosaic floors of roman Villa del Casale: Principal component analysis on spectrophotometric and colorimetric data. Journal of Cultural Heritage, 15(1), 92-97. doi:10.1016/j.culher.2012.12.004Faella, G., Frunzio, G., Guadagnuolo, M., Donadio, A., & Ferri, L. (2012). The Church of the Nativity in Bethlehem: Non-destructive tests for the structural knowledge. Journal of Cultural Heritage, 13(4), e27-e41. doi:10.1016/j.culher.2012.10.014La Gennusa, M., Rizzo, G., Scaccianoce, G., & Nicoletti, F. (2005). Control of indoor environments in heritage buildings: experimental measurements in an old Italian museum and proposal of a methodology. Journal of Cultural Heritage, 6(2), 147-155. doi:10.1016/j.culher.2005.03.001Hygrochron Temperature/Humidity Logger iButton with 8KB Data-Log Memoryhttp://datasheets.maxim-ic.com/en/ds/DS1923.pdfTemperature Logger iButton with 8KB Data-Log Memoryhttp://datasheets.maxim-ic.com/en/ds/DS1922L-DS1922T.pdfIBM Software. SPSS 16http://www-01.ibm.com/software/es/analytics/spss/García-Diego, F.-J., Fernández-Navajas, Á., Beltrán, P., & Merello, P. (2013). Study of the Effect of the Strategy of Heating on the Mudejar Church of Santa Maria in Ateca (Spain) for Preventive Conservation of the Altarpiece Surroundings. Sensors, 13(9), 11407-11423. doi:10.3390/s13091140

Characterization of temperature gradients according to height in a baroque church by means of wireless sensors

[EN] The baroque church of Saint Thomas and Saint Philip Neri (Valencia, Spain), which was built between 1727 and 1736, contains valuable paintings by renowned Spanish artists. Due to the considerable height of the central nave, the church can experience vertical temperature gradients. In order to investigate this issue, temperatures were recorded between August 2017 and February 2018 from a wireless monitoring system composed of 21 sensor nodes, which were located at different heights in the church from 2 to 13 m from the floor level. For characterizing the temperature at high, medium and low altitude heights, a novel methodology is proposed based on sparse Partial Least Squares regression (sPLS), Linear Discriminant Analysis (LDA), and the Holt-Winters method, among others, which were applied to a time series of temperature. This approach is helpful to discriminate temperature profiles according to sensor height. Once the vertical thermal gradients for each month were characterized, it was found that temperature reached the maximum correlation with sensor height in the period between August 10th and September 9th. Furthermore, the most important features from the time series that explain this correlation are the mean temperature and the mean of moving range. In the period mentioned, the vertical thermal gradient was estimated to be about 0.043 ºC/m, which implies a difference of 0.47 ºC on average between sensor nodes at 2 m from the floor with respect to the upper ones located at 13 m from the floor level. The gradient was estimated as the slope from a linear regression model using height and hourly mean temperature as the predictor and response, respectively. This gradient is consistent with similar reported studies. The fact that such gradient was only found in one month suggests that the mechanisms of dust deposition on walls involved in vertical thermal gradients are not important in this case regarding the preventive conservation of artworks. Furthermore, the methodology proposed here was useful to discriminate the time series at high, medium and low altitude levels. This approach can be useful when a set of sensors is installed for microclimate monitoring in churches, cathedrals, and other historical buildings, at different levels and positions.This project received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 814624.Ramírez, S.; Zarzo Castelló, M.; Perles, A.; García Diego, FJ. (2021). Characterization of temperature gradients according to height in a baroque church by means of wireless sensors. Sensors. 21(20):1-35. https://doi.org/10.3390/s21206921S135212

Corrosion prediction of metallic cultural heritage assets by EIS

Electrochemical Impedance Spectroscopy (EIS) was used to predict corrosion behaviour of metallic Cultural Heritage assets in two monitoring campaigns: 1) an iron bar chain exposed indoor from over 500 years in the Notre Dame Cathedral in Amiens (France); and 2) a large weathering steel sculpture exposed outdoor from tens of years in Ferrara (Italy). The EIS portable instrument employed was battery operated. In situ EIS measurements on the iron chain could be used to investigate the phenomena involved in the electrochemical interfaces among various corrosion products and assess and predict their corrosion behaviour in different areas of the Cathedral. Meanwhile, the sculpture of weathering steel, like most outdoor artefacts, showed rust layers of different chemical composition and colour depending on the orientation of metal plates. The EIS monitoring campaign was carried out on different areas of the artefact surface, allowing assessment of their protective effectiveness. Results of EIS measurements evidenced how employing a simple test that could be performed in situ without damaging the artefacts surface is possible to quickly gain knowledge of the conservation state of an artefact and highlight potential danger conditions

Design of a Hybrid (Wired/Wireless) Acquisition Data System for Monitoring of Cultural Heritage Physical Parameters in Smart Cities

Preventive conservation represents a working method and combination of techniques which helps in determining and controlling the deterioration process of cultural heritage in order to take the necessary actions before it occurs. It is acknowledged as important, both in terms of preserving and also reducing the cost of future conservation measures. Therefore, long-term monitoring of physical parameters influencing cultural heritage is necessary. In the context of Smart Cities, monitoring of cultural heritage is of interest in order to perform future comparative studies and load information into the cloud that will be useful for the conservation of other heritage sites. In this paper the development of an economical and appropriate acquisition data system combining wired and wireless communication, as well as third party hardware for increased versatility, is presented. The device allows monitoring a complex network of points with high sampling frequency, with wired sensors in a 1-wire bus and a wireless centralized system recording data for monitoring of physical parameters, as well as the future possibility of attaching an alarm system or sending data over the Internet. This has been possible with the development of three board's designs and more than 5000 algorithm lines. System tests have shown an adequate system operation.The authors acknowledge the collaboration of Rosa Maria Rodriguez y Belen Villanueva, superior and management technicians of Blasco Ibanez Museum-House respectively. This work was partially supported by the Spanish Government (Ministerio de Economia y Competitividad) under projects HAR2013-47895-C2-1-P and HAR2013-47895-C2-2-P.García Diego, FJ.; Esteban, B.; Merello Giménez, P. (2015). Design of a Hybrid (Wired/Wireless) Acquisition Data System for Monitoring of Cultural Heritage Physical Parameters in Smart Cities. Sensors. 15(4):7246-7266. doi:10.3390/s150407246S7246726615

A Statistical Methodology for Classifying Time Series in the Context of Climatic Data

[ES] De acuerdo con las regulaciones europeas y muchos estudios científicos, es necesario monitorear y analizar las condiciones microclimáticas en museos o edificios, para preservar las obras de arte en ellos. Con el objetivo de ofrecer herramientas para el monitoreo de las condiciones climáticas en este tipo de edificios, en esta tesis doctoral se propone una nueva metodología estadística para clasificar series temporales de parámetros climáticos como la temperatura y humedad relativa. La metodología consiste en aplicar un método de clasificación usando variables que se computan a partir de las series de tiempos. Los dos primeros métodos de clasificación son versiones conocidas de métodos sparse PLS que no se habían aplicado a datos correlacionados en el tiempo. El tercer método es una nueva propuesta que usa dos algoritmos conocidos. Los métodos de clasificación se basan en diferentes versiones de un método sparse de análisis discriminante de mínimos cuadra- dos parciales PLS (sPLS-DA, SPLSDA y sPLS) y análisis discriminante lineal (LDA). Las variables que los métodos de clasificación usan como input, corresponden a parámetros estimados a partir de distintos modelos, métodos y funciones del área de las series de tiempo, por ejemplo, modelo ARIMA estacional, modelo ARIMA- TGARCH estacional, método estacional Holt-Winters, función de densidad espectral, función de autocorrelación (ACF), función de autocorrelación parcial (PACF), rango móvil (MR), entre otras funciones. También fueron utilizadas algunas variables que se utilizan en el campo de la astronomía para clasificar estrellas. En los casos que a priori no hubo información de los clusters de las series de tiempos, las dos primeras componentes de un análisis de componentes principales (PCA) fueron utilizadas por el algoritmo k- means para identificar posibles clusters de las series de tiempo. Adicionalmente, los resultados del método sPLS-DA fueron comparados con los del algoritmo random forest. Tres bases de datos de series de tiempos de humedad relativa o de temperatura fueron analizadas. Los clusters de las series de tiempos se analizaron de acuerdo a diferentes zonas o diferentes niveles de alturas donde fueron instalados sensores para el monitoreo de las condiciones climáticas en los 3 edificios.El algoritmo random forest y las diferentes versiones del método sparse PLS fueron útiles para identificar las variables más importantes en la clasificación de las series de tiempos. Los resultados de sPLS-DA y random forest fueron muy similares cuando se usaron como variables de entrada las calculadas a partir del método Holt-Winters o a partir de funciones aplicadas a las series de tiempo. Aunque los resultados del método random forest fueron levemente mejores que los encontrados por sPLS-DA en cuanto a las tasas de error de clasificación, los resultados de sPLS- DA fueron más fáciles de interpretar. Cuando las diferentes versiones del método sparse PLS utilizaron variables resultantes del método Holt-Winters, los clusters de las series de tiempo fueron mejor discriminados. Entre las diferentes versiones del método sparse PLS, la versión sPLS con LDA obtuvo la mejor discriminación de las series de tiempo, con un menor valor de la tasa de error de clasificación, y utilizando el menor o segundo menor número de variables.En esta tesis doctoral se propone usar una versión sparse de PLS (sPLS-DA, o sPLS con LDA) con variables calculadas a partir de series de tiempo para la clasificación de éstas. Al aplicar la metodología a las distintas bases de datos estudiadas, se encontraron modelos parsimoniosos, con pocas variables, y se obtuvo una discriminación satisfactoria de los diferentes clusters de las series de tiempo con fácil interpretación. La metodología propuesta puede ser útil para caracterizar las distintas zonas o alturas en museos o edificios históricos de acuerdo con sus condiciones climáticas, con el objetivo de prevenir problemas de conservación con las obras de arte.[CA] D'acord amb les regulacions europees i molts estudis científics, és necessari monitorar i analitzar les condiciones microclimàtiques en museus i en edificis similars, per a preservar les obres d'art que s'exposen en ells. Amb l'objectiu d'oferir eines per al monitoratge de les condicions climàtiques en aquesta mena d'edificis, en aquesta tesi es proposa una nova metodologia estadística per a classificar series temporals de paràmetres climàtics com la temperatura i humitat relativa.La metodologia consisteix a aplicar un mètode de classificació usant variables que es computen a partir de les sèries de temps. Els dos primers mètodes de classificació són versions conegudes de mètodes sparse PLS que no s'havien aplicat adades correlacionades en el temps. El tercer mètode és una nova proposta que usados algorismes coneguts. Els mètodes de classificació es basen en diferents versions d'un mètode sparse d'anàlisi discriminant de mínims quadrats parcials PLS (sPLS-DA, SPLSDA i sPLS) i anàlisi discriminant lineal (LDA). Les variables queels mètodes de classificació usen com a input, corresponen a paràmetres estimats a partir de diferents models, mètodes i funcions de l'àrea de les sèries de temps, per exemple, model ARIMA estacional, model ARIMA-TGARCH estacional, mètode estacional Holt-Winters, funció de densitat espectral, funció d'autocorrelació (ACF), funció d'autocorrelació parcial (PACF), rang mòbil (MR), entre altres funcions. També van ser utilitzades algunes variables que s'utilitzen en el camp de l'astronomia per a classificar estreles. En els casos que a priori no va haver-hi información dels clústers de les sèries de temps, les dues primeres components d'una anàlisi de components principals (PCA) van ser utilitzades per l'algorisme k-means per a identificar possibles clústers de les sèries de temps. Addicionalment, els resultats del mètode sPLS-DA van ser comparats amb els de l'algorisme random forest.Tres bases de dades de sèries de temps d'humitat relativa o de temperatura varen ser analitzades. Els clústers de les sèries de temps es van analitzar d'acord a diferents zones o diferents nivells d'altures on van ser instal·lats sensors per al monitoratge de les condicions climàtiques en els edificis.L'algorisme random forest i les diferents versions del mètode sparse PLS van ser útils per a identificar les variables més importants en la classificació de les series de temps. Els resultats de sPLS-DA i random forest van ser molt similars quan es van usar com a variables d'entrada les calculades a partir del mètode Holt-winters o a partir de funcions aplicades a les sèries de temps. Encara que els resultats del mètode random forest van ser lleument millors que els trobats per sPLS-DA quant a les taxes d'error de classificació, els resultats de sPLS-DA van ser més fàcils d'interpretar.Quan les diferents versions del mètode sparse PLS van utilitzar variables resultants del mètode Holt-Winters, els clústers de les sèries de temps van ser més ben discriminats. Entre les diferents versions del mètode sparse PLS, la versió sPLS amb LDA va obtindre la millor discriminació de les sèries de temps, amb un menor valor de la taxa d'error de classificació, i utilitzant el menor o segon menor nombre de variables.En aquesta tesi proposem usar una versió sparse de PLS (sPLS-DA, o sPLS amb LDA) amb variables calculades a partir de sèries de temps per a classificar series de temps. En aplicar la metodologia a les diferents bases de dades estudiades, es van trobar models parsimoniosos, amb poques variables, i varem obtindre una discriminació satisfactòria dels diferents clústers de les sèries de temps amb fácil interpretació. La metodologia proposada pot ser útil per a caracteritzar les diferents zones o altures en museus o edificis similars d'acord amb les seues condicions climàtiques, amb l'objectiu de previndre problemes amb les obres d'art.[EN] According to different European Standards and several studies, it is necessary to monitor and analyze the microclimatic conditions in museums and similar buildings, with the goal of preserving artworks. With the aim of offering tools to monitor the climatic conditions, a new statistical methodology for classifying time series of different climatic parameters, such as relative humidity and temperature, is pro- posed in this dissertation.The methodology consists of applying a classification method using variables that are computed from time series. The two first classification methods are ver- sions of known sparse methods which have not been applied to time dependent data. The third method is a new proposal that uses two known algorithms. These classification methods are based on different versions of sparse partial least squares discriminant analysis PLS (sPLS-DA, SPLSDA, and sPLS) and Linear Discriminant Analysis (LDA). The variables that are computed from time series, correspond to parameter estimates from functions, methods, or models commonly found in the area of time series, e.g., seasonal ARIMA model, seasonal ARIMA-TGARCH model, seasonal Holt-Winters method, spectral density function, autocorrelation function (ACF), partial autocorrelation function (PACF), moving range (MR), among others functions. Also, some variables employed in the field of astronomy (for classifying stars) were proposed.The methodology proposed consists of two parts. Firstly, different variables are computed applying the methods, models or functions mentioned above, to time series. Next, once the variables are calculated, they are used as input for a classification method like sPLS-DA, SPLSDA, or SPLS with LDA (new proposal). When there was no information about the clusters of the different time series, the first two components from principal component analysis (PCA) were used as input for k-means method for identifying possible clusters of time series. In addition, results from random forest algorithm were compared with results from sPLS-DA.This study analyzed three sets of time series of relative humidity or temperate, recorded in different buildings (Valencia's Cathedral, the archaeological site of L'Almoina, and the baroque church of Saint Thomas and Saint Philip Neri) in Valencia, Spain. The clusters of the time series were analyzed according to different zones or different levels of the sensor heights, for monitoring the climatic conditions in these buildings.Random forest algorithm and different versions of sparse PLS helped identifying the main variables for classifying the time series. When comparing the results from sPLS-DA and random forest, they were very similar for variables from seasonal Holt-Winters method and functions which were applied to the time series. The results from sPLS-DA were easier to interpret than results from random forest. When the different versions of sparse PLS used variables from seasonal Holt- Winters method as input, the clusters of the time series were identified effectively.The variables from seasonal Holt-Winters helped to obtain the best, or the second best results, according to the classification error rate. Among the different versions of sparse PLS proposed, sPLS with LDA helped to classify time series using a fewer number of variables with the lowest classification error rate.We propose using a version of sparse PLS (sPLS-DA, or sPLS with LDA) with variables computed from time series for classifying time series. For the different data sets studied, the methodology helped to produce parsimonious models with few variables, it achieved satisfactory discrimination of the different clusters of the time series which are easily interpreted. This methodology can be useful for characterizing and monitoring micro-climatic conditions in museums, or similar buildings, for preventing problems with artwork.I gratefully acknowledge the financial support of Pontificia Universidad Javeriana Cali – PUJ and Instituto Colombiano de Crédito Educativo y Estudios Técnicos en el Exterior – ICETEX who awarded me the scholarships ’Convenio de Capacitación para Docentes O. J. 086/17’ and ’Programa Crédito Pasaporte a la Ciencia ID 3595089 foco-reto salud’ respectively. The scholarships were essential for obtaining the Ph.D. Also, I gratefully acknowledge the financial support of the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 814624.Ramírez Buelvas, SM. (2022). A Statistical Methodology for Classifying Time Series in the Context of Climatic Data [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181123TESI

Optimization of historic buildings that house artefacts considering climate change

Historic buildings, and the artefacts that are usually kept within these buildings, are a living representation of the past and it is essential to ensure that future generations have access to this heritage. In order to accomplish this, it is necessary to determine the conditions that the buildings are in and, if needs be, to make the required changes in order to preserve our cultural heritage. In addition, the foreseen changes of the indoor climate caused by climate change can endanger the preservation of these artefacts, since they are prone to various types of decay depending on the existing indoor conditions. One way of counteracting these changes, is the application of passive retrofit measures. However, the guideline was that retrofit measures were hardly ever used in cultural heritage because they could cause the building to lose its authenticity. Nowadays, more and more cases of historic buildings are subject to this type of measures. Indeed, these measures can lead to positive outcomes, such as decreasing the energy consumption of the buildings or mitigating the effects of climate change, but the welfare of the cultural heritage must be ensured before these measured can be applied. Hence, the main aim of this thesis is to determine the potential of passive retrofit measures in mitigating the negative effects of climate change in the indoor climate of historic buildings, whilst accounting for the artefacts’ preservation requirements. For this reason, the indoor climate of a 13th century church in Lisbon was used to develop and validate a whole-building hygrothermal model. Then, the model was run using future weather files to determine the future indoor conditions, which were then assessed using a risk-based analysis and an adaptive thermal comfort model. Finally, the effects of the passive retrofit measures in the building’s energy consumption, the artefacts’ conservation metrics and the occupants’ thermal comfort were assessed. The future weather files were developed based on the methodology described in standard EN 15927-4 and in Skartveit and Olseth model, which divides the global radiation into its direct and diffuse components. In addition, a methodology that aims to make large-sized hygrothermal studies more time-efficient is also presented. This methodology was based in the studies developed in this thesis. It was shown that the conditions for the preservation of artefacts that are housed in historic buildings will worsen, especially in Mediterranean climates when compared to humid Continental and Oceanic climates. The tested retrofit measures can mitigate, up to a certain extent, the negative effects imposed by climate change in terms of artefacts’ conservation requirements. However, the Mediterranean climates do not have the same margin as the other tested climates. In addition, it was also shown that there is a positive outcome of implementing these measures in terms of energy saving potential. These savings will even be higher if these measures are combined with a more adequate relative humidity and temperature setpoint strategy.Os edifícios históricos, e os artefactos que geralmente são guardados no interior destes edifícios, são uma representação viva do passado e é fundamental garantir que as gerações futuras também têm acesso ao património cultural. Para isso, é necessário determinar as condições interiores destes edifícios e, se necessário, aplicar as alterações necessárias de forma a promover a preservação do património. Além disso, as mudanças expectáveis dos climas internos causadas pelas alterações climáticas podem pôr em risco a preservação destes artefactos, uma vez que estes são propensos a vários tipos de deterioração consoante as condições internas. Uma forma de combater as mudanças expectáveis do clima interior deste tipo de edifico é a aplicação de medidas de reabilitação passivas. No entanto, era prática comum a sua aplicação em edifícios históricos ser muito restrita, uma vez que podiam provocar a perda de autenticidade destes edifícios. Actualmente é cada vez mais usual a aplicação destas medidas, que podem ter resultados bastante positivos, como a diminuição do consumo de energia dos edifícios ou a mitigação dos efeitos das alterações climáticas. No entanto, é necessário garantir que o património não sofre danos com a sua aplicação. O principal objectivo desta tese é determinar o potencial de mitigação dos efeitos negativos impostos pelas alterações climáticas no clima interior de edifícios históricos através do recurso a medidas de reabilitação passivas, tendo em conta os requisitos de preservação dos artefactos. Por este motivo, o clima interno de uma igreja do século XIII em Lisboa foi utilizado para desenvolver e validar um modelo higrotérmico. Numa fase subsequente o modelo foi corrido para ficheiros climáticos futuros de forma a determinar as condições internas futuras, que foram avaliadas recorrendo a uma análise de risco e a um modelo de conforto térmico adaptável. Por fim, foi avaliado o efeito das medidas de reabilitação passivas no consumo de energia do edifício, nas métricas de conservação dos artefactos e no conforto térmico dos ocupantes do edifício. Os ficheiros climáticos futuros foram construídos com base na metodologia descrita na norma EN 15927-4 e no modelo Skartveit and Olseth, que permite subdividir a radiação global na componente directa e difusa. É também apresentada uma metodologia que visa tornar os estudos higrotérmicos com inúmeros casos mais eficiente em termos temporais. Esta metodologia baseou-se estudos desenvolvidos nesta tese de doutoramento. Ficou demonstrado que as condições de preservação de artefactos guardados no interior de edifícios históricos vão piorar, especialmente em climas mediterrâneos quando comparados com climas húmidos continentais e oceânicos. As medidas de reabilitação passivas testadas podem mitigar, até certo ponto, os efeitos negativos provocados pelas alterações climáticas em termos de conservação de artefactos. No entanto, os climas mediterrâneos não têm a mesma margem que os outros climas testados. Além disso, também foi demonstrado que a implementação destas medidas apresenta um resultado positivo em termos de poupança energética. No entanto, esta poupança será ainda maior se estas medidas forem combinadas com uma estratégia de controlo de temperatura e humidade relativa mais adequada