Multivariate optimization of a GC–MS method for determination of sixteen priority polycyclic aromatic hydrocarbons in environmental samples

Abstract

This paper describes the development and optimization, by using multivariate analysis, of a GC -MS-SIM method for evaluation of the 16 polyaromatic hydrocarbons considered as priority pollutants in atmospheric particulate material by the US EPA. In order to assure an adequate separation in the shortest analysis time, a multivariate design was used to set the conditions of the oven temperature program. The optimization process was carried out using factorial fractional design and BoxBehnken design. The following factors were evaluated: initial temperature, temperature rate #1, intermediary temperature, temperature rate #2, and final temperature. The optimized conditions were set at: 708C (2 min) 2008C (308C/min, 5 min) 3008C (58C/min, 1.67 min). Moreover, we have also optimized the injector temperature as 3108C and sampling time as 0.8 min. The total analysis time was 33 min. Validation of GC -MS-SIM yielded satisfactory results for repetitivity of the detector response and retention times, and linearity of calibration curves. LOD were established as 0.13 -0.34 ng/mL (peak area) and 0.18 -0.72 ng/mL (peak height). The method has been shown to be appropriate for the analysis of samples of atmospheric particulate material and/or other environmental matrices.

Quantification and source identification of atmospheric particulate polycyclic aromatic hydrocarbons and their dry deposition fluxes at three sites in Salvador Basin, Brazil, impacted by mobile and stationary sources

“…30 GC-MS-SIM analyses were performed as described elsewhere. 31 Briefly, a model QP2010 GC-MS system with …”

Multivariate optimization of headspace-GC for the determination of monoaromatic compounds (benzene, toluene, ethylbenzene, and xylenes) in waters and wastewaters

“…Therefore, in order to improve the process and, consequently, increase the analytical sensitivity and reduce the total analysis time, it is recommended that such parameters are optimized [22][23][24]. In general, the optimization process is performed by a univariate approach, i.e., the classic system in which the factors (design variables) are analyzed individually.…”

“…Some experimental parameters can directly influence the efficiency of the HS extraction method, such as temperature, extraction time, sample volume, and salinity. Therefore, in order to improve the process and, consequently, increase the analytical sensitivity and reduce the total analysis time, it is recommended that such parameters are optimized . In general, the optimization process is performed by a univariate approach, i.e., the classic system in which the factors (design variables) are analyzed individually.…”

Analysis of Parent/Nitrated Polycyclic Aromatic Hydrocarbons in Particulate Matter 2.5 Based on Femtosecond Ionization Mass Spectrometry

“…Multidimensional gas chromatography (e.g., GC×GC/TOF-MS) is more useful because of its better separation resolution and has been applied for the measurement of an aerosol extract [7]. A technique involving electron ionization (EI) is most frequently used as an ionization source in MS [8]. In this case, many fragment ions appear, especially for NPAHs, which makes measuring the target molecule a difficult task.…”