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Comparative Study of Computational Models for Reducing Air Pollution Through the Generation of Negative Ions

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Submitted:

07 May 2021

Posted:

10 May 2021

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Abstract
Today, air quality is one of the global concerns that governments are facing. One of the main air pollutants is the particulate matter (PM) that affects human health. This article presents the modeling of a purification system by means of negative air ions (NAIs) for air pollutant removal, using computational intelligence methods. The system uses a high voltage booster output to ionize air molecules from stainless steel electrodes; its particle-capturing efficiency reaches up to 97%. With two devices (5 x 2 x 2.5 cm), 2 trillion negative ions are produced per second, and the particulate matter (PM 2.5) can be reduced from 999 to 0 mg / m3 in a period of approximately 5 to 7 minutes (in a 40 x 40 x 40 cm acrylic chamber). This negative ion generator is a viable and sustainable alternative to reduce polluting emissions, with beneficial effects on human health.
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Subject: Engineering  -   Automotive Engineering
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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