Chemical exposure in household dust poses potential risks to human health but has been studied incompletely thus far. Most analytical studies have focused on one or several compound classes, with analysis performed by either liquid or gas chromatography coupled with mass spectrometry (LC-MS or GC-MS). However, a comprehensive investigation of individual dust samples is missing. The present study comprehensively characterizes chemicals in dust by applying a combination of target, suspect, and nontarget screening approaches using both LC and GC with quadrupole time-of-flight (Q/TOF) MS. First, the extraction method was optimized to streamline detection of LC-Q/TOF and GC-Q/TOF amenable compounds and was successfully validated with over 100 target compounds. Nontarget screening with GC-Q/TOF was done by spectral deconvolution followed by a library search. Suspect screening by LC-Q/TOF was carried out with an accurate mass spectral library. Finally, LC-Q/TOF nontarget screening was carried out by extracting molecular features, acquiring tandem mass spectrometric (MS/MS) spectra, and performing compound identification by use of in silico fragmentation software tools. In total, 271 chemicals could be detected in 38 dust samples, 163 of which could be unambiguously confirmed by a reference standard. Many of them, such as the plastic leachable 7,9-di- tert-butyl-1-oxaspiro(4,5)deca-6,9-diene-2,8-dione (CAS 82304-66-3) and three organofluorine compounds, are of emerging concern and their presence in dust has been underestimated. Advantages and drawbacks of the different approaches and analytical instruments are critically discussed.

Efficient strategies are required to implement comprehensive suspect screening methods using high-resolution mass spectrometry within environmental monitoring campaigns. In this study, both liquid and gas chromatography time-of-flight mass spectrometry (LC-QTOF-MS and GC-QTOF-MS) were used to screen for >5000 target and suspect compounds in the Sacramento-San Joaquin River Delta in Northern California. LC-QTOF-MS data were acquired in All-Ions fragmentation mode in both positive and negative electrospray ionization (ESI). LC suspects were identified using two accurate mass LC-QTOF-MS/MS libraries containing pesticides, pharmaceuticals, and other environmental contaminants and a custom exact mass database with predicted transformation products (TPs). The additional fragment information from the All-Ions acquisition improved the confirmation of the compound identity, with a low false positive rate (9%). Overall, 25 targets, 73 suspects, and 5 TPs were detected. GC-QTOF-MS extracts were run in negative chemical ionization (NCI) for 21 targets (mainly pyrethroids) at sub-ng/L levels. For suspect screening, extracts were rerun in electron ionization (EI) mode with a retention time locked method using a GC-QTOF-MS pesticide library (containing exact mass fragments and retention times). Sixteen targets and 42 suspects were detected, of which 12 and 17, respectively, were not identified by LC-ESI-QTOF-MS. The results highlight the importance of analyzing water samples using multiple separation techniques and in multiple ionization modes to obtain a comprehensive chemical contaminant profile. The investigated river delta experiences significant pesticide inputs, leading to environmentally critical concentrations during rain events.