Title | Development of quantitative screen for 1550 chemicals with GC-MS. |
Publication Type | Journal Article |
Year of Publication | 2018 |
Authors | Bergmann AJ, Points GL, Scott RP, Wilson GR, Anderson KA |
Journal | Anal Bioanal Chem |
Volume | 410 |
Issue | 13 |
Pagination | 3101-3110 |
Date Published | 2018 May |
ISSN | 1618-2650 |
With hundreds of thousands of chemicals in the environment, effective monitoring requires high-throughput analytical techniques. This paper presents a quantitative screening method for 1550 chemicals based on statistical modeling of responses with identification and integration performed using deconvolution reporting software. The method was evaluated with representative environmental samples. We tested biological extracts, low-density polyethylene, and silicone passive sampling devices spiked with known concentrations of 196 representative chemicals. A multiple linear regression (R = 0.80) was developed with molecular weight, logP, polar surface area, and fractional ion abundance to predict chemical responses within a factor of 2.5. Linearity beyond the calibration had R > 0.97 for three orders of magnitude. Median limits of quantitation were estimated to be 201 pg/μL (1.9× standard deviation). The number of detected chemicals and the accuracy of quantitation were similar for environmental samples and standard solutions. To our knowledge, this is the most precise method for the largest number of semi-volatile organic chemicals lacking authentic standards. Accessible instrumentation and software make this method cost effective in quantifying a large, customizable list of chemicals. When paired with silicone wristband passive samplers, this quantitative screen will be very useful for epidemiology where binning of concentrations is common. Graphical abstract A multiple linear regression of chemical responses measured with GC-MS allowed quantitation of 1550 chemicals in samples such as silicone wristbands. | |
10.1007/s00216-018-0997-7 | |
Alternate Journal | Anal Bioanal Chem |
PubMed ID | 29552732 |
PubMed Central ID | PMC5910463 |
Grant List | T32 ES007060 / ES / NIEHS NIH HHS / United States T32-ES007060-32 / / National Institute of Environmental Health Sciences / |