Profiling naphthenic acids in produced water using hollow fiber liquid-phase microextraction combined with gas chromatography coupled to Fourier transform Orbitrap mass spectrometry

Exploring accurate mass measurements in pixel-based chemometrics: Advancing coffee classification with GC-HRMS-A proof of concept study

This paper presents a study that assesses the application of chemometrics for classifying coffee samples in a quality control context. High-resolution and accurate mass measurements were utilized as input for pixel-based orthogonal partial least squares discriminant analysis (OPLS-DA) models. The compositional data were acquired through a fully automated workflow combining headspace solid-phase microextraction and gas chromatography-high-resolution mass spectrometry (GC-HRMS) using an FT-Orbitrap® mass analyzer. A workflow centered on accurate mass measurements was successfully utilized for group-type analysis, offering an alternative to methods relying solely on MS similarity searches. The predictive models underwent thorough evaluation, demonstrating robust multivariate classification performance. Five key coffee attributes, bitterness, acidity, body, intensity, and roasting level were successfully predicted using GC-HRMS data. The results revealed strong predictive accuracy across all models, ranging from 88.9 % (bitterness) to 94.4 % (roasting level). This study represents a significant advancement in automating methods for coffee quality control, notably increasing the predictive ability of the models compared to existing literature.

Sample preparation, analytical characterization, monitoring, risk assessment and treatment of naphthenic acids in industrial wastewater and surrounding water impacted by unconventional petroleum production

Industrial extraction of unconventional petroleum results in notable volumes of oil sands process water (OSPW), containing elevated concentrations of naphthenic acids (NAs). The presence of NAs represents an intricate amalgamation of dissolved organic constituents, thereby presenting a notable hurdle for the domain of environmental analytical chemistry. There is growing concern about monitoring the potential seepage of OSPW NAs into nearby groundwater and river water. This review summarizes recent studies on sample preparation, characterization, monitoring, risk assessment, and treatment of NAs in industrial wastewater and surrounding water. Sample preparation approaches, such as liquid-liquid extraction, solid phase microextraction, and solid phase extraction, are crucial in isolating chemical standards, performing molecular level analysis, assessing aquatic toxicity, monitoring, and treating OSPW. Instrument techniques for NAs analysis were reviewed to cover different injection modes, ionization sources, and mass analyzers. Recent studies of transfer and transformation of NAs provide insights to differentiate between anthropogenic and natural bitumen-derived sources of NAs. In addition, related risk assessment and treatment studies were also present for elucidation of environmental implication and reclamation strategies. The synthesis of the current state of scientific knowledge presented in this review targets government regulators, academic researchers, and industrial scientists with interests spanning analytical chemistry, toxicology, and wastewater management.

Classification of produced water samples using class-oriented chemometrics and comprehensive two-dimensional gas chromatography coupled to mass spectrometry

Produced water (PW) is a type of wastewater that arises during oil and gas production. Due to its potential environmental impact, PW is one of the most closely monitored forms of wastewater in the petroleum industry. The total oil and grease (TOG) content in the water is a crucial parameter for assessing the environmental impact of PW. Traditional methods for analyzing TOG in PW can be time-consuming and may not be compatible with green chemistry principles. In this study, an alternative method for classifying PW samples is proposed using a one-class classifier (OCC) model, which has proven useful for classification problems. To achieve this goal, headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography (GC×GC) were employed to obtain TOG profiles from PW. A series of simulated PW samples containing TOG were generated using a mixture design comprising four petrochemicals at concentrations ranging from 10 mg L-1 to 50 mg L-1. The polydimethylsiloxane (PDMS) fiber showed the most representative extraction of analytes. The optimization of the HS-SPME method was performed using a Doehlert design with two variables, and the final conditions were set at 80 °C and 70 min for extraction temperature and time, respectively. A pixel-based data approach was used to implement data-driven soft independent modeling by class analogy (DD-SIMCA). Although DD-SIMCA is a developing area in GC×GC studies, the proposed model produced outstanding results with a sensitivity of 94.3 %, specificity of 95.0 %, and accuracy of 94.5 %, considering the complex and broad compositional range of the modeled mixtures. These findings demonstrated the effectiveness of the OCC model approach in classifying PW samples according to environmental regulations.

Analysis of naphthenic acids in produced water samples by capillary electrophoresis-mass spectrometry

A capillary electrophoresis-mass spectrometry method was used to analyze naphthenic acids in produced water samples. It was possible to detect cyclopentanecarboxylic, benzoic, cyclohexanebutyric, 1-naphthoic, decanoic, 3,5-dimethyladamantane-1-carboxylic, 9-anthracenecarboxylic, and pentadecanoic acids within ca. 13 min using a buffer composed of 40 mmol/L ammonium hydroxide, 32 mmol/L acetic acid and 20% v/v isopropyl alcohol, pH 8.6. The proposed method showed good repeatability, with relative standard deviation (RSD) values of 6.6% for the sum of the peak areas and less than 2% for the analysis time. In the interday analysis, the RSD values for the sum of the peak areas and migration time were 10.3% and 10%, respectively. The developed method demonstrated linear behavior in the concentration range between 5 and 50 mg/L for benzoic, decanoic, 3,5-dimethyladamantane-1-carboxylic and 9-anthracenecarboxylic acids, and between 10 and 50 mg/L for cyclopentanecarboxylic, cyclohexanebutyric, 1- naphthoic, and pentadecanoic acids. The detection limits values ranged from 0.31 to 1.64 mg/L. Six produced water samples were analyzed and it was possible to identify and quantify cyclopentanecarboxylic, benzoic, cyclohexanebutyric, and decanoic acids. The concentrations varied between 4.8 and 98.9 mg/L, proving effective in the application of complex samples.

Multidimensional Gas Chromatography: Benefits and Considerations for Current and Prospective Users

Two-dimensional gas chromatography (GC×GC) offers improved separation power for complex samples containing hundreds to thousands of analytes. However, several considerations must be made to determine whether multidimensional gas chromatography (MDGC) is the logical instrument choice to answer a particular scientific question, including, but not limited to, whether the analysis is targeted or non-targeted, the number of analytes of interest, and the presence of interferences that are coeluted, as well as any potential regulatory or industrial constraints. Currently, MDGC remains daunting for many users because of data complexity and the limited tools commercially available, which are critical for improving the accessibility of MDGC. Herein, we discuss considerations that may assist analysts, laboratory managers, regulatory agents, instrument and software vendors, and those interested in understanding the applicability of 2D-GC for the scientific question being investigated.

Advanced tuning of the ion management parameters in GC × GC-HRMS using a Fourier transform Orbitrap mass analyzer for pixel-based data handling and multivariate analysis

GC × GC investigations are well known to generate a substantial amount of information-rich and structurally complex data, requiring advanced data processing strategies like chemometrics. Many workflows are available for data handling and processing, such as the peak-table and pixel-based approaches. The goal of this work is to present a solution based on method development to solve the missing pixel problem that may be encountered in experiments performed with GC and GC × GC coupled to the Fourier transform orbital ion trap (FT-Orbitrap) mass analyzer. Data input is vital for pixel-based chemometric analyses, as some post-processing solutions may lead to significant loss of chemical information in the data set. Hence, a key requisite is that the chemical information is consistently indexed in the data arrays for proper pixel-based data handling and analysis. In this study, we carefully evaluated the ion management parameters to preserve the intrinsic structure and information of the data arrays of the GC × GC-FT-Orbitrap for future pixel-oriented chemometric analysis. The most acceptable conditions yielded acquisition rates up to 42.6 spectra per s, while a routine setting of 24.7 Hz was successfully employed in analyses of different petroleum fractions, producing both consistent tensor sizes and acceptable peak reconstructions. A data acquisition rate of 24.7 spectra per s and a mass resolving power of 15 000 allowed the resolution of a mass split of only 0.004 Da - which is an interesting configuration for challenging applications in petroleomics. Using such advanced settings, the missing pixel problem was reduced from up to 30% to much less than 0.04% of the data array dimension. Thus, the proposed configuration can be employed in studies that require pixel-oriented multivariate data analysis.