This model estimates pollutant removal in V-shaped filters integrated with catalytic technologies, suggesting feasible filtration solutions.
Atmospheric pollution from particulate matter, volatile organic compounds and greenhouse gases is a critical environmental and public health issue, leading to respiratory diseases and climate change. A potential mitigation strategy involves utilising ventilation systems, which process large volumes of indoor and outdoor air and remove particulate pollutants through filtration. However, the integration of catalytic technologies with filters in ventilation systems remains underexplored, despite their potential to simultaneously remove particulate matter and gases, as seen in flue gas treatment and automotive exhaust systems. In this study, we develop a predictive, long-wave model for V-shaped filters, with and without separators. The model, validated against experimental and numerical data, provides a framework for enhancing flow rates by increasing fibre diameter and porosity while reducing aspect ratio and filter thickness. These changes lead to increased permeability, which lowers energy requirements. However, they also reduce the pollutant removal efficiency, highlighting the trade-off between flow, filtration performance and operational costs. Leveraging the long-wave model alongside experimental results, we estimate the maximum potential removal rate (2×10⁻⁴ GtPM2.5, 2×10⁻³ GtNOₓ, 9×10⁻³ GtCH₄ per year) and minimum cost (\7×10⁴ per tNOₓ, \2×10⁴ per tCH₄) if a billion V-shaped filters integrated with catalytic enhancements were deployed in operation. These findings highlight the feasibility of catalytic filters as a scalable, high-efficiency solution for improving air quality and mitigating atmospheric pollution.
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Tomlinson et al. (2025) studied this question.
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