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Experimental validation of adsorption filter model under dynamic VOC concentrations: Prediction of long-term efficiency

  • Research Article
  • Indoor/Outdoor Airflow and Air Quality
  • Published:
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Abstract

Indoor volatile organic compound (VOC) concentrations are often dynamic because the ventilation and emission rates of VOC usually change. Adsorption filters used for air purification may operate with a capacity that fluctuates with unsteady VOC concentrations in buildings. Modeling the dynamic interactions between adsorption filters and indoor air is crucial for predicting their performance under real-world conditions. This study presents a numerical model of partially reversible adsorption equilibrium coupled with a mass transfer model to create a predictive model for adsorption efficiency in environments with dynamic VOC concentrations. A honeycomb adsorption filter for benzene adsorption was simulated and tested, including the breakthrough and purging curve and the long-term efficiency in an experimental chamber with dynamic concentrations. The results reveal that the curve generated with the partially reversible adsorption equilibrium model closely aligns with the measured one. Furthermore, the model was coupled with a chamber model and the simulation results were compared with those calculated using the filter model with a single adsorption isotherm. When VOCs were emitted intermittently in the chamber and there was sufficient ventilation, the concentration peaks in the chamber derived from the models with different assumptions on adsorption reversibility were significantly different from each other. Moreover, it was observed that the reversible adsorption capacity of the filter was crucial for long-term operation in rooms with dynamic concentration. Despite the reversible adsorption capacity constituting only 6.7% of the total adsorption capacity of the tested filter, it contributes to a significant “peak shaving and valley filling” effect, even when the irreversible adsorption capacity is saturated. The adsorption reversibility should be taken as an important parameter for selecting adsorbents for dynamic concentration conditions.

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Abbreviations

A :

surface area of adsorbent particles (m2)

A f :

windward area of the adsorption filter (m2)

C a,max :

irreversible adsorption capacity (mg/m3)

C a,t :

cumulative concentration of irreversible adsorbate (mg/m3)

C d,max :

reversible adsorption capacity (mg/m3)

C d,t :

cumulative concentration of reversible adsorbate (mg/m3)

C gas :

concentration of gaseous benzene (mg/m3)

C max :

gaseous benzene concentration at which the activated carbon was saturated before desorption (mg/m3)

C p :

concentration of sorbed-phase benzene in pellet

C r :

sorbed-phase benzene concentration at the surface of the pellets

C s :

equivalent concentration of adsorbate in REV (mg/m3)

C s,max :

total adsorption capacity (mg/m3)

D eff :

effective diffusion coefficient

D x :

axial diffusion coefficient through the filter (m2/s)

h m :

convective mass transfer coefficient (m/s)

K a :

partition coefficient between the gas phase and irreversible adsorbate ((mg/g)/(mg/m3))

K d :

partition coefficient between the gas phase and reversible adsorbate ((mg/g)/(mg/m3))

K p :

partition coefficient between the gas phase and adsorbate ((mg/g)/(mg/m3))

K s :

partition coefficient between the concentrations in sorbent and air

k v :

total decay constant (min−1)

M adsorbent :

mass of activated carbon in REV (g)

M s :

total adsorption capacity per unit mass of activated carbon (mg/g)

M s,max :

adsorbed benzene concentration before desorption (mg/g)

M s,t :

current adsorption capacity (mg/g)

Q in :

benzene injection rate (mg/s)

r :

radius of the pellets

r d :

reversible adsorption proportion of the total adsorption capacity

R :

apparent mass transfer resistance (s/m3)

ν :

superficial air velocity (m/s)

V chamber :

volume of the test chamber (m3)

V REV :

representative elementary volume (m3)

ε :

void fraction of the filter

η t :

single-pass efficiency of the adsorption filter

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Acknowledgements

This research has been supported by the National Natural Science Foundation of China under grant No. 52108089.

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Authors and Affiliations

  1. School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Ruiyan Zhang, Ziying Li, **angyuan Guan, **n Wang & Fei Wang

  2. School of Mechanical Engineering, Tongji University, Shanghai, 200092, China

    Lingjie Zeng & Zhenhai Li

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  1. Ruiyan Zhang
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  2. Ziying Li
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  3. **angyuan Guan
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  4. **n Wang
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  5. Fei Wang
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Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Ruiyan Zhang, Ziying Li, **angyuan Guan, **n Wang, Fei Wang, Lingjie Zeng and Zhenhai Li. The first draft of the manuscript was written by Ruiyan Zhang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Lingjie Zeng.

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12273_2024_1135_MOESM1_ESM.pdf

Electronic Supplementary Material: Experimental validation of adsorption filter model under dynamic VOC concentrations: Prediction of long-term efficiency

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Zhang, R., Li, Z., Guan, X. et al. Experimental validation of adsorption filter model under dynamic VOC concentrations: Prediction of long-term efficiency. Build. Simul. (2024). https://doi.org/10.1007/s12273-024-1135-4

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