Methods for probability distributions estimation of indoor environmental parameters and long-term IEQ assessment

To overcome the difficulties in comparing enormous time series for indoor environmental parameters and make use of technological developments in previous research, this study considers environmental parameters from a new perspective, their probability density functions (PDFs). PDFs are combined with existing indoor environmental quality (IEQ) mathematical models to assess the long-term IEQ. Two methodologies were developed: probability distribution estimation of indoor environmental parameters and long-term IEQ distribution assessment based on the Monte Carlo method. The effectiveness of the developed methodologies was illustrated in a three-month IEQ assessment of an office. PDFs were obtained with specific mathematical expressions for the three-month air temperature, sound level and illuminance. The three-month distributions for thermal, visual, acoustic and overall environmental quality were presented using eight previous IEQ mathematical models. PDFs have the advantage of using only a few main parameters instead of an enormous time series to explain the behaviour and characteristics of environmental parameters. PDFs can also potentially determine the commonalities of environmental distributions for different buildings. The obtained IEQ distributions present a straightforward and comprehensive impression of the long-term IEQ, rather than a simple index.