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Towards a better understanding of adsorption of indoor air pollutants in porous media—From mechanistic model to molecular simulation

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Abstract

Adsorption has been the most feasible and reliable technology to tackle indoor gaseous pollutants. Theoretical analysis is required for a better understanding of adsorption in addition to trial-and-error experiments. A systematic overview of the conventional mechanistic models for adsorption equilibrium (capacity) and kinetics (transport), which are the two key ingredients needed for a complete understanding of adsorption, was presented first. In spite of the valuable guidance those models have provided, their dependences on lumped or unsubstantiated parameters and deficiency in molecular-level information of adsorption processes have become bottlenecks of the adsorption research. Molecular simulation was then introduced as a powerful tool to overcome the limitations of the conventional models by providing the details at molecular level that are intractable for trial-and-error experiments or the conventional modeling to access. The bottom-up scheme of molecular simulation with minimal assumptions is particularly suitable for exploring the underlying mechanisms of adsorption. The basic principles and key procedures of molecular simulation were introduced, followed by the recent progress of molecular simulation study on indoor air pollutants and its comparison with the conventional models.

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Acknowledgements

The research was supported by the national key project of the Ministry of Science and Technology, China, on “Green Buildings and Building Industrialization” through Grant No. 2016YFC0700500.

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  1. Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, 300072, China

    Lumeng Liu, Junjie Liu & Jingjing Pei

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  1. Lumeng Liu
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  2. Junjie Liu
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Correspondence to Jingjing Pei.

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Liu, L., Liu, J. & Pei, J. Towards a better understanding of adsorption of indoor air pollutants in porous media—From mechanistic model to molecular simulation. Build. Simul. 11, 997–1010 (2018). https://doi.org/10.1007/s12273-018-0445-9

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