Advertisement

The Study of Historic Indoor Microclimate

Chapter

Abstract

The study and investigation of HIM from the starting point of actual microclimate AIM is the subject of this chapter. This can be done through (1) direct investigation, with probes and measurements; (2) indirect investigation, with modeling tools; and (3) historic studies and surveys. Direct investigation allows to study actual microclimate with instrumentations, interviews, and questionnaires, given that the physical information is not sufficient to comprehend the modalities of management, affluence, and usage of the current spaces. Questionnaires are particularly useful to acquire information that wouldn’t be otherwise accessible and to interpret the recorded data, with peaks and anomalies. Indirect investigation uses instruments and software of building simulations, and the main modeling tools and general indication to use them for the study of Historic Indoor Microclimate are described. Indirect investigation includes studies that can be conducted with the analysis of historical climatic data, calibration, and projection with respect to the needs or design and restorations of virtual environment.

References

  1. Acot P (2006) Catastrophes climatiques, désastres sociaux. Presses Universitaires de France, Paris. ISBN 9782130552635CrossRefGoogle Scholar
  2. Acot P (2009) Histoire du climat: Du Big Bang aux catastrophes climatiques. TEMPUS/PERRIN, Paris. ISBN 978-2262030285Google Scholar
  3. Ahmad MW, Mourshed M, Mundow D, Sisinni M, Rezgui Y (2016) Building energy metering and environmental monitoring—a state-of-the-art review and directions for future research. Energ Buildings 120:85–102CrossRefGoogle Scholar
  4. Ascione F, de Rossi F, Vanoli GP (2011) Energy retrofit of historical buildings: theoretical and experimental investigations for the modelling of reliable performance scenarios. Energ Buildings 43:1925–1936CrossRefGoogle Scholar
  5. Balocco C, Grazzini G (2007) Plant refurbishment in historical buildings turned into museum. Energ Buildings 39:693–701CrossRefGoogle Scholar
  6. Behringer W (2004) Witches and witch-hunts: a global history (a cultural history of climate). Polity, Cambridge. ISBN 978-0745645285Google Scholar
  7. Bernardi A, Todorov V, Hiristova J (2000) Microclimatic analysis in St. Stephen’s church, Nessebar, Bulgaria, after the invention for the conservation of frescoes. J Cult Herit 1(3):281–286CrossRefGoogle Scholar
  8. Bradley RS, Hughes MK, Diaz HF (2003) Climate in medieval time. Science 302:404–405CrossRefGoogle Scholar
  9. Brazdil R, Pfister C, Wanner H, von Storch H, Lutterbacher J (2005) Historical climatology in Europe—the state of the art. Clim Change 70(3):363–430CrossRefGoogle Scholar
  10. Camuffo D, Bertolin C (2012) The earliest temperature observations in the world: the Medici Network (1654–1670). Clim Change 11:335–363CrossRefGoogle Scholar
  11. Camuffo D, Jones P (eds) (2002) Improved understanding of past climatic variability from early daily European instrumental sources. Springer/Kluwer Academic, Dordrecht. ISBN 9789401003711Google Scholar
  12. Camuffo D, Brimblecombe P, Van Grieken R, Busse H, Sturaro G, Val-entino A (1999) Indoor air quality at the Corrier museum, Venice, Italy. Sci Total Environ 236(1–3):135–152CrossRefGoogle Scholar
  13. Camuffo D, Bernardi A, Sturaro G, Valentino A (2002) The microclimate inside the Pollaiolo and Botticelli rooms in the Uffizi gallery. Florence J Cul Herit 3(2):155–161CrossRefGoogle Scholar
  14. Corgnati SP, Perino M (2013) CFD application to optimise the ventilation strategy of Senate Room at Palazzo Madama in Turin (Italy). J Cult Herit 14(1):62–69CrossRefGoogle Scholar
  15. Fabbri K (2015) Assessment of the influence of the thermal environment using subjective judgement scales. In: Indoor thermal comfort perception: a questionnaire approach focusing on children. Springer, Cham. 9783319186511CrossRefGoogle Scholar
  16. Giuliani M, Henze CP, Florita AR (2016) Modelling and calibration of a high-mass historic building for reducing the prebound effect in energy assessment. Energ Buildings 116:434–448CrossRefGoogle Scholar
  17. Hensen JLM, Lamberts R (2011) Building performance simulation for design and operation. Spon Press, LondonGoogle Scholar
  18. Hoseggen R et al (2008) Building simulation as an assisting tool in decision making. Case study: with or without a double-skin façade? Energ Buildings 40:821–827CrossRefGoogle Scholar
  19. La 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. J Cult Herit 6(2):147–155CrossRefGoogle Scholar
  20. Litti G, Audenaert A, Braet J (2013a) Energy retrofitting in architectural heritage, possible risks due to the missing of a specific legislative and methodological protocol. In: Proceedings of the European conference on sustainability, energy and environment 2013, pp 127–137. ISSN 2188-1146Google Scholar
  21. Litti G, Audenaert A, Braet J, Lauriks L (2013b) Energy environmental monitoring in historical buildings: a simplified methodology for modeling realistic retrofitting scenarios: the case study of Schoonselhof Kasteel in Antwerp (Belgium). In: Built heritage 2013 monitoring conservation management, pp 1075–1083Google Scholar
  22. Litti G, Audenaert A, Braet J, Fabbri K, Weeren A (2015) Synthetic scan and simultaneous index aimed at the indoor environmental quality evaluation and certification for people and artworks in heritage buildings. Energy Procedia 78:1365–1370CrossRefGoogle Scholar
  23. Lucchi E (2016) Multidisciplinary risk-based analysis for supporting the decision making process on conservation, energy efficiency, and human comfort in museum buildings. J Cult Herit 22:1079–1089CrossRefGoogle Scholar
  24. Martínez-Molina A, Tort-Ausina I, Cho S, Vivancos JL (2016) Energy efficiency and thermal comfort in historic buildings: a review. Renew Sustain Energy Rev 61:70–85CrossRefGoogle Scholar
  25. Monetti V, Davin E, Fabrizio E, André P, Filippi M (2015) Calibration of building energy simulation models based on optimization: a case study. Energy Procedia 78:2971–2976. 6th international building physics conference, IBPC 2015CrossRefGoogle Scholar
  26. Moschen R, Kuhl N, Peters S, Vos H, Lucke A (2011) Temperature variability at Durres Maar, Germany during the migration period and at high medieval times, inferred from stable carbon isotopes of Sphagnum cellulose. Clim Past 7:1011–1026CrossRefGoogle Scholar
  27. Mustafaraj G, Marini D, Costa A, Keane M (2014) Model calibration for building energy efficiency simulation. Appl Energy 130:72–85CrossRefGoogle Scholar
  28. Rijal HB et al (2007) Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings. Energ Buildings 39:823–836CrossRefGoogle Scholar
  29. Royapoor M, Roskilly T (2015) Building model calibration using energy and environmental data. Energ Buildings 94:109–120CrossRefGoogle Scholar
  30. Segrè G, Cannillo T (2005) A qualcuno piace freddo, Temperatura, vita, materia. Bollati Boringhieri, Turin. ISBN 978-8833915852Google Scholar
  31. US DOE (2016) EnergyPlus version 8.5.0 (Online). http://www.energyplus.gov/. Accessed 18 Aug 2016
  32. Vieites E, Vassileva I, Arias JE (2015) European initiatives towards improving the energy efficiency in existing and historic buildings. Energy Procedia 75:1679–1685CrossRefGoogle Scholar
  33. Yanga Z, Becerik-Gerber B (2015) A model calibration framework for simultaneous multi-level building energy simulation. Appl Energy 149:415–431CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of ArchitectureUniversity of BolognaBolognaItaly

Personalised recommendations