Dependencies of the indoor climate on the course of the seasons and derivation of regressions from long‐term measurements. (13th June 2022)

• Record Type: Journal Article
• Authors: Hofmann, Markus; Geyer, Christoph; Kornadt, Oliver
• Is Part Of: Indoor air. Volume 32:Number 6(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-06-13
• Subjects: dew point temperature -- indoor climate -- indoor climate model -- long‐term measurement -- moisture load -- user behavior -- window ventilation; Indoor air pollution -- Periodicals; Sick building syndrome -- Periodicals; Ventilation -- Periodicals; 613.5
• DOI: 10.1111/ina.13058
• Languages: English
• ISSNs: 0905-6947

Abstract

Abstract: A building's indoor climate is an essential input variable for a variety of building physics computational models, simulations, and analyses. Precise knowledge of the indoor climate is necessary to minimize the risk of mold or moisture damage and is required to ensure minimum heat insulation standards in buildings. Detailed data are especially necessary for the progressive application of transient calculations, for example, concerning thermal comfort or energy consumption. While the properties of building materials and the (local) outdoor climate are known, only rudimentary information about the dynamic indoor climate is available. Most existing information in the literature about indoor climate is fairly general and forgoes a differentiation between climatic region, occupancy profile, and the utilization of rooms. In this paper, we report on indoor climate measurements in naturally ventilated apartments over a period of 1 year. The measurement results complement the existing data to provide accurate indoor climate data in buildings. The measured values of indoor temperature and relative humidity serve to derive the dew point temperature and moisture load whereby dynamic time‐dependent regression functions are determined for these parameters. The evaluations are carried out separately according to room use. The comparison of living rooms and bedrooms indicates a great influence of room use on the indoor climate in residential buildings. The determined indoor climate model can be used for the planning of buildings and simulations. The classification into living rooms and bedrooms makes it possible to take user behavior into account more realistically in building physics simulations. The minimum thermal insulation in residential buildings can also be checked and designed based on realistic data. The prediction interval describes the limits in which residential rooms are free of damage with a high probability. In this way, the indoor climate model describes an approach to examine and evaluate simulation results regarding condensation risk and mold damage in naturally ventilated rooms.