Long-term simulation for predicting indoor air pollutant concentration considering pollutant distribution based on concept of CRPS index

Abstract

Modern people spend most of their time indoors and so are chronically exposed to indoor air pollutants. To identify the health effects of pollutant exposure, it is necessary to understand the changes over time in indoor pollutant concentrations. There are two approaches for simulating pollutant concentration changes: mass balance model, computational fluid dynamics (CFD). Although the mass balance model is suitable for long-term simulation because it is simple, there is a limit to the detailed analysis considering concentration distribution. CFD can simulate the distribution of indoor air pollutants, but long-term analyses require too many computational resources. This study proposed a novel simulation method that couples the mass balance model with the contribution ratio of pollutant sources (CRPS) index, which indicates the individual impact of all pollutant sources and is extracted from CFD result. By introducing the CRPS index, long-term pollutant concentrations can be calculated as fast as the mass balance model while considering the pollutant distribution like CFD. The method was validated using previous experimental data. The case study was conducted and simulated changes in pollutant concentrations in a new residential unit for one week. The results showed that the CRPS-coupled method was different from conventional methods in that it more realistically calculates pollutant concentrations using relatively little computational resources.