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Diffusive and subdiffusive dynamics of indoor microclimate: a time series modeling.

Monika Maciejewska1, Andrzej Szczurek, Grzegorz Sikora

  • 1Institute of Air Conditioning and District Heating, Wroclaw University of Technology, Wybrzeże Wyspiańskiego 27, Wrocław 50-370, Poland. monika.maciejewska@pwr.wroc.pl

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 4, 2012
PubMed
Summary

Indoor temperature and relative humidity dynamics differ significantly. Temperature behavior shifts with occupancy, while humidity remains consistently diffusive, impacting microclimate monitoring accuracy.

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Area of Science:

  • Building Science
  • Environmental Physics
  • Data Analysis

Background:

  • Modern society necessitates understanding indoor microclimates as people spend ~90% of time indoors.
  • Temperature and relative humidity are key indoor microclimate parameters, often assumed to behave similarly.

Purpose of the Study:

  • To analyze the distinct dynamics and dependency structures of indoor temperature and relative humidity time series, excluding deterministic components.
  • To investigate how building occupancy influences these microclimate parameters.

Main Methods:

  • Utilized mean square displacement, autoregressive integrated moving average (ARIMA) models, and anomalous diffusion analysis.
  • Analyzed indoor environmental data from five locations in an office building over approximately one week.

Main Results:

  • Indoor temperature exhibited a transition from diffusive to subdiffusive behavior correlating with changes in building occupancy (weekday vs. weekend).
  • Relative humidity consistently displayed diffusive behavior throughout the monitoring period.
  • Temperature and humidity datasets showed different dependency structures, as indicated by distinct ARIMA models.

Conclusions:

  • Indoor temperature and relative humidity exhibit fundamentally different dynamic behaviors and dependency structures.
  • The findings highlight the complexity of indoor air conditions and propose an improved approach for microclimate monitoring.
  • Preservation of dynamics and dependency structures in the space domain was observed for each parameter.