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Predicting Future Condition and Conservation Costs from Modelling Improvements to the Indoor Environment: The Monumental Munch-Paintings in the University of Oslo’s Aula Assembly Hall
5 references·5 citing·36 second hop
Predicting Future Condition and Conservation Costs from Modelling Improvements to the Indoor Environment: The Monumental Munch-Paintings in the University of Oslo’s Aula Assembly Hall (2019)Predicting Future Condition and Conservat…Assessment of indoor air quality and the risk of damage to cultural heritage objects using MEMORI®dosimetry (2016)Assessment of indoor air qual…A proposed method to assess the damage risk of future climate change to museum objects in historic buildings (2012)A proposed method to assess t…Pollution monitoring by dosimetry and passive diffusion sampling for evaluation of environmental conditions for paintings in microclimate frames (2010)Pollution monitoring by dosim…Significance 2.0: a guide to assessing the significance of collections (2009)Significance 2.0: a guide to …Economics of Dust (2007)Economics of DustThe role of SVOCs in the initial film formation and soiling of unvarnished paintings (2023)The role of SVOCs in the init…Modelling of the deterioration and conservation costs of polychrome painted wood in two Norwegian medieval stone churches (2023)Modelling of the deterioratio…MACHINE LEARNING MODEL FOR THE PREDICTION OF CONDITION OF MUSEUM OBJECTS (2023)MACHINE LEARNING MODEL FOR TH…Hyperspectral Imaging Analyses of Cleaning Tests on Edvard Munch's Monumental Aula Paintings (2022)Hyperspectral Imaging Analyse…Estimation of the historical dry deposition of air pollution indoors to the monumental paintings by Edvard Munch in the University Aula, in Oslo, Norway (2022)Estimation of the historical …The National Trust Manual of House-Keeping (1986)Clothing as a source of fibres within museums (2000)The Distribution of Soiling by Coarse Particulate Matter in the Museum Environment (2001)The importance of long-term hygrothermal assessment of museum spaces: method and application in a permanent exhibition in a historical building (2018)FTIR surface analysis for conservation (2020)Air Quality and Energy Use in a Museum (2025)Microclimate for Cultural Heritage (1998)Microclimate for Cultural Heritage (2000)The atlas of climate change impact on European cultural heritage : scientific analysis and management strategies (2010)The capacity to adapt to climate change at heritage sites—The development of a conceptual framework (2014)Microclimatic monitoring of the Duomo (Milan Cathedral): Risks-based analysis for the conservation of its cultural heritage (2018)Risk Mapping for the Sustainable Protection of Cultural Heritage in Extreme Changing Environments (2020)Guidelines on Pollution Control in Museum Buildings (2000)Airborne pollutants in museums, galleries and archives : risk assessment, control strategies, and preservation management (2002)Corrosivity measurements of indoor museum environments using lead coupons as dosimeters (2008)Environmentally induced colour change during natural degradation of selected polymers (2013)Raman spectroscopic study of the degradation of a middle age mural painting: the role of agricultural activities (2014)The Indoor Environment of a Modern Museum Building, The Sainsbury Centre for Visual Arts, Norwich, UK (1999)Assessment of the impact of particulate dry deposition on soiling of indoor cultural heritage objects found in churches and museums/libraries (2019)Method Development to Assess the Ventilated and Nonventilated Sources of Indoor Dust Deposits, Applied in a Museum (2024)Near Infrared Reflectance Imaging Spectroscopy to Map Paint Binders In Situ on Illuminated Manuscripts (2012)Visible and infrared imaging spectroscopy of paintings and improved reflectography (2016)Materials and techniques of Islamic manuscripts (2018)Allowable microclimatic variations for painted wood (2013)Simplified assessment method for environmental and energy quality in museum buildings (2016)Fracture saturation in paintings makes them less vulnerable to environmental variations in museums (2020)Indoor air pollution: Effects on cultural and historic materials (1985)Accelerated VS Natural Aging: Effect of Aging Conditions on the Aging Process of Cellulose (1995)Indexing reliability for condition survey data (2007)Dose–response functions for historic paper (2011)Protecting contemporary cultural soundscapes as intangible cultural heritage: sounds of Istanbul (2016)De-growing museum collections for new heritage futures (2018)Situating (in)significance (2020)Monitoring the accumulated water soluble airborne compounds deposited on surfaces of showcases and walls in museums, archives and historical buildings (2017)Indoor air pollution impact on cultural heritage in an urban and a rural location in Romania: the National military museum in Bucharest and the Tismana monastery in Gorj County (2018)Crystalline Deposits in New Display Cases at the Rijksmuseum: Characterisation and Origin (2020)
this work references cited by second hop

References

  • 2012A proposed method to assess the damage risk of future climate change to museum objects in historic buildings154 cited
  • 2009Significance 2.0: a guide to assessing the significance of collections73 cited
  • 2010Pollution monitoring by dosimetry and passive diffusion sampling for evaluation of environmental conditions for paintings in microclimate frames39 cited
  • 2016Assessment of indoor air quality and the risk of damage to cultural heritage objects using MEMORI®dosimetry32 cited
  • 2007Economics of Dust22 cited

Cited by

  • 2022Hyperspectral Imaging Analyses of Cleaning Tests on Edvard Munch's Monumental Aula Paintings21 cited
  • 2022Estimation of the historical dry deposition of air pollution indoors to the monumental paintings by Edvard Munch in the University Aula, in Oslo, Norway6 cited
  • 2023Modelling of the deterioration and conservation costs of polychrome painted wood in two Norwegian medieval stone churches4 cited
  • 2023The role of SVOCs in the initial film formation and soiling of unvarnished paintings1 cited
  • 2023MACHINE LEARNING MODEL FOR THE PREDICTION OF CONDITION OF MUSEUM OBJECTS1 cited

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