The monitoring of some micro-pollutants is routinary because of their potential toxic activity and of normative regulation, but focusing only on some targeted compounds can divert analysts and researchers from identifying pollution macro-events associated to untargeted compounds. Routine analysis of micro-pollutants, as PAHs, in fast scan GC-MS produces Single Ion Monitoring (SIM) chromatograms used for quantitative determination of target compounds but also a Total Ion Current (TIC) signal which can potentially contain interesting unrevealed information. This is specially true when thermal desorption from solid samples as air particulate matter filters is used as pretreatment method; TD/GC-MS transfers analytes to the separation column without discarding some/part of the compounds. The aim of this study is to report the setup of an experimental and data analysis procedure adequate for disclosing interesting data from raw GCMS data collections acquired during routine monitoring. In this communication we present a 3 month daily PAHs routine monitoring near an incinerator in a Friuli Venezia Giulia chair production district in which we collected 120 samples of PM10 by quartz filter sampling accordingly to EN12341. A series of raw data (retention time, peak area, peak height, peak width, MW, CAS number) were acquired directly from the data analysis software (meanwhile quantifying PAHs) using the “autointegration” and “MS library search” functions. These data were handled within R free statistical computing environment (http://cran.rproject. org), using a home-made script to filter and intercomparing chromatograms by peak properties. In this way we were able, starting from over 5000 peaks to discriminate, beyond PAHs, 21 relevant peaks present in a great number of samples. Using MS library search reports we were able to identify three molecules with high correspondence to the MS database, which can be related to activities in the sampling site: a plasticizer, a phtalate and an erbicide. These compounds were quantified using corresponding commercial standards.

Advances in TD/GC-MS untargeted compound analysis on particulate matter beyond PAHs routine monitoring

LICEN, SABINA;TOLLOI, ARIANNA;ADAMI, GIANPIERO;COZZUTTO, SERGIO;BARBIERI, PIERLUIGI
2013-01-01

Abstract

The monitoring of some micro-pollutants is routinary because of their potential toxic activity and of normative regulation, but focusing only on some targeted compounds can divert analysts and researchers from identifying pollution macro-events associated to untargeted compounds. Routine analysis of micro-pollutants, as PAHs, in fast scan GC-MS produces Single Ion Monitoring (SIM) chromatograms used for quantitative determination of target compounds but also a Total Ion Current (TIC) signal which can potentially contain interesting unrevealed information. This is specially true when thermal desorption from solid samples as air particulate matter filters is used as pretreatment method; TD/GC-MS transfers analytes to the separation column without discarding some/part of the compounds. The aim of this study is to report the setup of an experimental and data analysis procedure adequate for disclosing interesting data from raw GCMS data collections acquired during routine monitoring. In this communication we present a 3 month daily PAHs routine monitoring near an incinerator in a Friuli Venezia Giulia chair production district in which we collected 120 samples of PM10 by quartz filter sampling accordingly to EN12341. A series of raw data (retention time, peak area, peak height, peak width, MW, CAS number) were acquired directly from the data analysis software (meanwhile quantifying PAHs) using the “autointegration” and “MS library search” functions. These data were handled within R free statistical computing environment (http://cran.rproject. org), using a home-made script to filter and intercomparing chromatograms by peak properties. In this way we were able, starting from over 5000 peaks to discriminate, beyond PAHs, 21 relevant peaks present in a great number of samples. Using MS library search reports we were able to identify three molecules with high correspondence to the MS database, which can be related to activities in the sampling site: a plasticizer, a phtalate and an erbicide. These compounds were quantified using corresponding commercial standards.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2834053
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