Development of a novel methodology for indoor emission source identification

Publication: Research - peer-reviewJournal article – Annual report year: 2011

  • Author: Han, K.H.

    Syracuse University, Department of Mechanical and Aerospace Engineering,

  • Author: Zhang, J.S.

    Syracuse University, Department of Mechanical and Aerospace Engineering,

  • Author: Knudsen, H.N.

    Aalborg University

  • Author: Wargocki, Pawel

    Section for Indoor Environment, Department of Civil Engineering, Technical University of Denmark, Denmark

  • Author: Chen, H.

    Boise State University, Department of Electrical and Computer Engineering

  • Author: Varshney, P.K.

    Syracuse University, Department of Electrical Engineering and Computer Science

  • Author: Guo, B.

    Syracuse University, Department of Mechanical and Aerospace Engineering

View graph of relations

The objective of this study was to develop and evaluate a methodology to identify individual sources of emissions based on the measurements of mixed air samples and the emission signatures of individual materials previously determined by Proton Transfer Reaction-Mass Spectrometry (PTR-MS), an on-line analytical device. The methodology based on signal processing principles was developed by employing the method of multiple regression least squares (MRLS) and a normalization technique. Samples of nine typical building materials were tested individually and in combination, including carpet, ceiling material, gypsum board, linoleum, two paints, polyolefine, PVC and wood. Volatile Organic Compound (VOC) emissions from each material were measured in a 50-liter small-scale chamber. Chamber air was sampled by PTR-MS to establish a database of emission signatures unique to each individual material. The same task was performed to measure combined emissions from material mixtures for the application and validation of the developed signal separation method. Results showed that the proposed method could identify the individual sources under laboratory conditions with two, three, five and seven materials present. Further experiments and investigation are needed for cases where the relative emission rates among different compounds may change over a long-term period.
Original languageEnglish
JournalAtmospheric Environment
Publication date2011
Volume45
Issue18
Pages3034-3045
ISSN1352-2310
DOIs
StatePublished
CitationsWeb of Science® Times Cited: 12

Keywords

  • Signal processing, Source identification, PTR-MS, VOC, Materials emission signature
Download as:
Download as PDF
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
Word

ID: 5549640