FAKTORER BAKOM MÖGELTILLVÄXT PÅ NÄÄS SLOTT

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Date

2025-06-25

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Abstract

With climate change, the temperature and relative humidity in Sweden are increasing. The majority of historical environments lack protection against this increase, which also increases the risk of mold infestation in these environments. One of these environments is Nääs Slott, in which several rooms have recurring mold growth on objects and furniture. By examining one of the rooms in the castle that is in the risk zone or has mold growth, factors behind the mold growth can be investigated in order to create a basis for future actions against mold. This investigation focuses on the Butler’s room, which shows both risk factors behind and developed mold growth. The investigation also focuses on furniture with wooden parts and wooden objects, which can be broken down by mold. Previous studies in both cultural heritage and building science, as well as theory within the subject have shown that RH, temperature, nutrient availability, airflow and microclimate are the main limiting factors measured to investigate mold growth. In this study, three zones in the Butler’s room were examined. In these zones, there are wooden objects or furniture with wooden parts that are affected by mold. These objects are a drawer, a cupboard and a bed with a wooden base. To investigate the limiting factors, data loggers were placed to measure RH and temperature in each zone and each object was visually examined to establish how wood acts as a substrate for mold. In addition, previous and ongoing measures taken to minimize risks for mold growth are analyzed. Finally, future measures are proposed for the room, such as optimizing the use of dehumidifiers and reducing the use of fan heaters to minimize the risk of mold growth.

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Uppsats för avläggande av filosofie kandidatexamen med huvudområdet kulturvård med inriktning mot konservering 2025, 180 hp Grundnivå ISSN 1101-3303; ISRN GU/KUV 2025-06-08 1

Keywords

Relative humidity, temperature, preventive conservation, hygrothermic data

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