Recent epidemiological studies linking indoor exposure and health consequence relied mostly on the annual-averaged indoor exposure concentration from a steady-state modelling rather than that aggregated from a dynamic modelling approach.We hypotheses that such simplification could lead to a bias on the derivation of the indoor concentration, which could further propogage on health assessment.Methods
The increase of envelope air tightness and installation of mechanical ventilation with effective filtration are considered as two building ventilation retrofit strategies to reduce indoor PM2.5 exposure to outdoor origin. The integrated modelling framework considering health benefits and energy costs of different intervention strategies is employed for a representative urban residential building in five Chinese mega cities being exposed to different levels of outdoor air pollution.Three indoor air quality models (annual-average steady-state, hourly steady-state, and dynanic) are adopted to compare their accuracies and error propagations.Results
The comparison of the modelling methodologies shows that modelling indoor concentrations by the annual average steady-state method could lead to relative error from −10.5% to 18% in some cases. The relative errors in indoor PM2.5 modelling caused by simplification methodologies can be greatly enlarged in the assessment of health and economic impacts (from −524% to 249%).The total economic benefits for building ventilation interventions are largest in Shenyang (~800 yuan/capita), but marginal or even negative in Chengdu and Guangzhou. For Beijing and Shanghai, to achieve significant benefits, the air tightness level should be at least National Level 7 while the filtration efficiency should be no less than 90% if mechanical ventilation systems are installed.Conclusion
We have modelled the health benefit and energy cost for different building ventilation retrofits in five mega cities in China using three types of indoor air quality models. Our modelling results show that there are large errors using annual-averaged indoor exposure concentration especially for the assessment of health and economic consequence.