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In countries suffering from heavy ambient air pollution, ventilation is a problem, as ventilation intakes outdoor air pollutants, such as particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), while removing indoor air pollutants. Thus, it is important to identify appropriate ventilation-purification strategies to build healthy indoor environments with low energy consumption. This study reports the comparison of two sets of strategies, i.e., mechanical ventilation with filters and natural ventilation with indoor air cleaners, in respect to energy consumption and the PM2.5 and carbon dioxide (CO2) exposure of occupants in a typical apartment in Beijing, China. A dynamic mass balance model was employed to calculate the PM2.5 and CO2 exposure concentrations, while the energy consumption of heating and cooling was simulated with the Designer’s Simulation Toolkit. It was found that natural ventilation with air cleaners provided lower PM2.5 exposure compared with that of mechanical ventilation with filters; however, mechanical ventilation achieved a lower CO2 exposure concentration. The annual cooling, heating, and fan energy consumption of natural ventilation strategies are lower than those of mechanical ventilation strategies. With respect to natural ventilation, an infiltration rate of 0.3-0.4 h-1 was the preferred setting, which led to low PM2.5 and CO2 exposure with lower energy consumption. The basic requirements for controlling indoor PM2.5 could be met if the threshold is set at 25 μg/m3. The results provide guidelines on how to combine multiple ventilation purification strategies to improve indoor air quality with lower energy usage.

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Publication history
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Acknowledgements

Publication history

Received: 09 June 2020
Accepted: 19 July 2020
Published: 22 August 2020
Issue date: June 2021

Copyright

© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020

Acknowledgements

This research was supported by the China Postdoctoral Science Foundation (No. 2019M650013), Fundamental Research Funds for the Central Universities (No. FRF-TP-18-083A1), and National Natural Science Foundation of China (No. 51908032). Professor Da Yan and Dr. Jingjing An helped to build the energy simulation model, and we greatly appreciate their assistance.

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