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University of Toronto

Development of Nontargeted Screening Algorithms for Indoor Contaminants

Abstract

dc:description.abstract

Humans spend most of their lives indoors, but there are thousands of chemical contaminants in indoor environments and the majority of these remain undetected. The focus of this thesis was to develop methods for nontargeted screening and prioritization of previously unreported indoor chemical contaminants using high-resolution mass spectrometry. To achieve this, a one – stop suspect screening algorithm was developed incorporating retention time prediction, isotopic peak calculation and in silico MS2 prediction. The algorithm was benchmarked for halogenated compounds and was further applied to screen for previously unrecognized indoor contaminants. Among 39 chlorinated compounds detected, 18 previously unrecognized azo dyes were detected as the biggest class of indoor chlorinated compounds (Chapter 2). To further characterize the indoor sources of these chlorinated compounds, various consumer products were collected from Toronto homes and screened for toxic halogenated contaminants with an emphasis on chlorinated paraffins. Chlorinated paraffin compounds were detected in 84 of 96 products analyzed, including electronic devices and plastic children’s toys, despite these compounds being prohibited for manufacture or import in Canada as of 2013 (Chapter 3). In addition to direct emission sources, the indirect sources of indoor contaminants formed through indoor reactions were investigated. To achieve this, an R package (‘indoortransformer’) was developed to predict indoor transformation products of organophosphorus compounds (OPCs). By further expanding the R package to incorporate in silico MS2 fragmentation prediction, 40 OPCs were detected in 23 house dust samples among which 24 OPCs were predicted to be formed through indoor reactions (Chapter 4). To systematically investigate the emission of contaminants from indoors, wastewater samples were collected over a 1.5 year period during the COVID-19 pandemic and screened against the ToxCast and Tox21 databases. Among 1037 ToxCast compounds, 43 were detected with high frequency plus 8 additional dyes and OPCs. Several plasticizers and disinfectants also showed an increase in concentration during periods of public lockdown (Chapter 5). This thesis provides a systematic exploration of the occurrence, source, reactions and temporal trends of many indoor contaminants. Future studies are warranted to expand the nontargeted screening methods developed in the current study to additional indoor compound classes.

Degree

thesis:*
Department dc:contributor.department
Chemistry
Year dc:date.issued
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kutarna, Steven
Advisor dc:contributor.advisor
  • Peng, Hui

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • Attribution-NonCommercial-NoDerivatives 4.0 International

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1807/128213
OAI identifier oai:identifier
oai:utoronto.scholaris.ca:1807/128213

Chain of custody

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University of Toronto
Base URL
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Last updated
2026-07-27
Source record
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citation

Kutarna, Steven. Development of Nontargeted Screening Algorithms for Indoor Contaminants. 2023. http://hdl.handle.net/1807/128213