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

Today, air quality is one of the global concerns that governments are facing. One of the main air pollutants is the particulate matter (PM) which affects human health. This article presents the modeling of a purification system by means of negative air ions (NAIs) for air pollutant removal, using co...

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Bibliographic Details
Main Authors: Paola Ortiz-Grisales, Julián Patiño-Murillo, Eduardo Duque-Grisales
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/13/13/7197
Description
Summary:Today, air quality is one of the global concerns that governments are facing. One of the main air pollutants is the particulate matter (PM) which 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 cm × 2 cm × 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/m<sup>3</sup> in a period of approximately 5 to 7 minutes (in a 40 cm × 40 cm × 40 cm acrylic chamber). This negative ion generator is a viable and sustainable alternative to reduce polluting emissions, with beneficial effects on human health.
ISSN:2071-1050