Evaluation of housing stock indoor air quality models: A review of data requirements and model performance

Abstract

To develop and evaluate housing strategies and interventions for improving indoor air quality (IAQ) at a city or national scale, housing stock IAQ models are required. Without such models, reliable prediction of residential indoor pollution concentrations and exposures at various spatial-temporal scales cannot be achieved. To address the areas not covered by past review articles in housing stock performance modelling, this paper presents the first comprehensive review of the housing stock IAQ models published during 2012–2020. Our review was carried out to achieve three outcomes: (1) to identify and summarize the fundamental IAQ modelling approaches including model assumptions, (2) to review the housing stock IAQ modelling methods (engineering and/or statistical), sampling methods, data sources in use and the underlying computation assumptions, and (3) to propose a descriptive framework and a performative matrix. The review resulted in a set of 11 key model attributes with which housing stock IAQ models can be evaluated in terms of data requirements and model performance. To improve robustness and accuracy in concentration and exposure predictions, future housing stock IAQ models should be developed to account for the dynamic interaction between heat transfer, inter-zone airflow and indoor contaminant transport through IAQ-Energy co-simulation.