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Characterization of indoor aerosol temporal variations for the real-time management of indoor air quality

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Author

  • Darius Ciuzas
  • Tadas Prasauskas
  • Edvinas Krugly
  • Ruta Sidaraviciute
  • Andrius Jurelionis
  • Lina Seduikyte
  • Violeta Kauneliene
  • Aneta Wierzbicka
  • Dainius Martuzevicius

Summary, in English

The study presents the characterization of dynamic patterns of indoor particulate matter (PM) during various pollution episodes for real-time IAQ management. The variation of PM concentrations was assessed for 20 indoor activities, including cooking related sources, other thermal sources, personal care and household products. The pollution episodes were modelled in full-scale test chamber representing a standard usual living room with the forced ventilation of 0.5 h(-1). In most of the pollution episodes, the maximum concentration of particles in exhaust air was reached within a few minutes. The most rapid increase in particle concentration was during thermal source episodes such as candle, cigarette, incense stick burning and cooking related sources, while the slowest decay of concentrations was associated with sources, emitting ultrafine particle precursors, such as furniture polisher spraying, floor wet mopping with detergent etc. Placement of the particle sensors in the ventilation exhaust vs. in the centre of the ceiling yielded comparable results for both measured maximum concentrations and temporal variations, indicating that both locations were suitable for the placement of sensors for the management of IAQ. The obtained data provides information that may be utilized considering measurements of aerosol particles as indicators for the real-time management of IAQ. (C) 2015 Elsevier Ltd. All rights reserved.

Publishing year

2015

Language

English

Pages

107-117

Publication/Series

Atmospheric Environment

Volume

118

Document type

Journal article

Publisher

Elsevier

Topic

  • Building Technologies

Keywords

  • Indoor air
  • Pollution sources
  • Particulate matter
  • Temporal variation
  • Real-time monitoring
  • Air quality management

Status

Published

ISBN/ISSN/Other

  • ISSN: 1352-2310