Energies (Jun 2020)

Development of Weighting Scheme for Indoor Air Quality Model Using a Multi-Attribute Decision Making Method

  • Michał Piasecki,
  • Krystyna Kostyrko

DOI
https://doi.org/10.3390/en13123120
Journal volume & issue
Vol. 13, no. 12
p. 3120

Abstract

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When planning the energy demand of ventilation, proper consideration should be given to the possible scenarios of indoor air quality and pollutant concentrations. The purpose of the present research is to create a practical method of prioritising indoor air pollutants, considering technical, economical and health aspects, in the Indoor Air Quality model (IAQ). In order to find the global weights for the combined IAQindex model sub-elements (in practice, air pollutant concentrations), the Multi-Criteria Decision Making (MCDM) approach is used. The authors have approached the problem of a weighting scheme in a model such as the complex model of the IAQ related to making decisions with many criteria and with the Multi-Attribute Decision Making MADM approach (specifically MCDM). The basis of the MADM method is a decision matrix constructed rationally by the authors, which includes six attributes: actual indoor air carbon dioxide concentration, total volatile organic compounds (TVOCs) and formaldehyde HCHO concentration, and their anthropogenic and construction product emissions to the indoor environment. The decision model of IAQindex includes five alternatives (possible situations), and the combination of pollutant concentration attributes with additional emission attributes is related to the indoor environment under specific situation. For defining the weights of criteria, the authors provide objective approaches: (i) entropy-based approach considering measuring the amount of information, and (ii) CRITIC, a statistic-based approach. The value of the presented method, i.e., the determination of global weights for IAQ components, is shown as a practical application to determine IAQ and the Indoor Environmental Quality (IEQ) index for an office building used as a case study.

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