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Automation of large-scale gaseous ozonation: a case study of textile and PPE decontamination

  • Emmanuel I. Epelle
  • , Mohammed Yaseen*
  • , Andrew Macfarlane
  • , Michael Cusack
  • , Anthony Burns
  • , Luc Rolland
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    98 Downloads (Pure)

    Abstract

    There is an ever-growing need in several industries to disinfect or sanitise products (i.e., to reduce or eliminate pathogenic microorganisms from their surfaces). Gaseous ozone has been widely applied for this purpose, particularly during the era of the COVID-19 pandemic. However, the large-scale deployment of this technology usually involves a manually-operated chamber, into which articles are loaded and subsequently unloaded after treatment—a batch process. Although the development of large-scale, automated and continuous ozonation equipment has hardly been reported in the literature, this has tremendous potential for industries seeking to decontaminate certain articles/products in a rapid and effective manner. In this paper, an overview of the design and implementation considerations for such an undertaking is evaluated. By presenting a case study for a developed automated system for clothing and personal protective equipment (PPE) disinfection, we provide key data regarding the automation procedure/design’s considerations, risks, material compatibility, safety, sustainability and process economics. Our analysis shows that the transfer time for garments between successive chambers and the agility of the sliding doors are crucial to achieving the desired throughput. The automated system is capable of effectively treating (20 ppm ozone for 4 mins) 20,000 garments within an 8-hour shift, based on a transfer time of 2 mins and a sliding door speed of 0.4 m/s. The flexibility of the system allows for variation in the concentration or exposure time, depending on the contamination level and the consequent decontamination efficiency desired. This flexibility significantly limits the degradation of the material during treatment. A return on investment of 47% is estimated for this novel system.
    Original languageEnglish
    Article number2216
    Number of pages19
    JournalSustainability
    Volume15
    Issue number3
    DOIs
    Publication statusPublished - 25 Jan 2023

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being
    2. SDG 6 - Clean Water and Sanitation
      SDG 6 Clean Water and Sanitation

    Keywords

    • ozone decontamination
    • automation
    • throughput enhancement
    • textile
    • PPE

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