Dynamics of carbon dioxide concentration in indoor air

Abstract

Carbon dioxide is an indicator of indoor air quality. A number of factors influence its concentration. Due to the fact that they all present time variability, CO2 concentration indoors considerably varies over time. In this work we focus on the dynamics of indoor CO2 concentration changes. We examine the dynamics of CO2 variation and use it as a source of information on the character of collective impact of factors on indoor air. The proposed method is based on mean square displacement analysis (MSD) applied to the segments of the time series of CO2 monitoring data. The segments are determined based on the introduced criterion for optimal sample size selection. The method was validated by showing that it reproduces the known stochastic dynamics of the simulated data set properly. From the real data analysis, we found that indoors the stochastic dynamics of CO2 concentration in time was mainly nonlinear. Moreover, it exhibited a cycle of change which could be associated with the daily variation of the collective influence of factors on indoor air. We intend to apply the method to other parameters of indoor air, aiming at developing a capability of describing the dynamics of indoor air as a complex system.