Class separation of buildings with high and low prevalence of SBS by principal component analysis

L. Pommer, J. Fick, B. Andersson, Jan Sundell, C. Nilsson, M. Sjoestroem, B. Stenberg

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    This method was able to separate buildings with high and low prevalence of SBS in two different classes using principal component analysis (PCA). Data from the Northern Swedish Office Illness Study describing the presence and level of chemical compounds in outdoor, supply and room air, respectively, were evaluated together with information about the buildings. The most complex model was able to separate 71% of the high prevalence buildings from the low prevalence buildings. The most important variables that separate the high prevalence buildings from the low prevalence buildings was a more frequent occurrence of a higher concentration of terpenoid compounds and ketones in the high prevalence buildings. Relative air humidity in supply and room air, and TVOC in outdoor and supply air and 10 building variables also contributed to the separation of low and high prevalence buildings.
    Original languageEnglish
    Title of host publicationProceedings of Indoor Air 2002
    Publication date2002
    Publication statusPublished - 2002
    Event9th International Conference on Indoor Air Quality and Climate - Monterey, CA, United States
    Duration: 30 Jun 20025 Jul 2002
    Conference number: 9
    http://www.indair.org/index_files/Page325.htm

    Conference

    Conference9th International Conference on Indoor Air Quality and Climate
    Number9
    Country/TerritoryUnited States
    CityMonterey, CA
    Period30/06/200205/07/2002
    Internet address

    Fingerprint

    Dive into the research topics of 'Class separation of buildings with high and low prevalence of SBS by principal component analysis'. Together they form a unique fingerprint.

    Cite this