Akademik Veri Yönetim Sistemi
Journal of Separation Science, cilt.48, sa.12, 2025 (SCI-Expanded, Scopus)
Wastewater-based epidemiology (WBE) concerns the analysis of human biomarkers in untreated sewage samples as indicators of diseases, exposure to pollutants, and population lifestyle. Smoking, in various forms, and its prevalence in society are essential aspects of such studies. Anatabine, anabasine, cotinine, and hydroxycotinine are the most well-known nicotine biomarkers, and the relation of their concentrations with the smoking prevalence has been used in WBE studies. Analysis of these compounds has been based on LC–MS following classical solid or liquid extractions. Regarding the complexity of the sewage samples, the final chromatograms are still plagued by a large number of contaminants, despite the use of tandem or high-resolution MS detectors. In this work, a novel headspace SPME-Arrow extraction method has been developed, optimized, and validated for determining four nicotine metabolites in raw sewage medium. A Box–Behnken design was used to assess the significance of temperature, pH and ionic strength as three factors influencing the extraction efficiency and also to optimize the experimental conditions. The effect of extraction time and its optimum value were determined individually. The optimized sample preparation method followed by GC–MS (SIM) was shown to be sensitive enough to analyze the analytes at their actual concentration levels (ng–µg L−1), thanks to ng L−1 LOQs and linear calibration up to 40 µg L−1. A raw sewage sample was also used to evaluate the accuracy and validate the method, with relative recoveries ranging from 87% to 103% for the spiked real sample at 400 ng L−1. The entire analytical procedure and the sample preparation step were assessed for their greenness, based on AGREE and AGREEprep models, respectively. Results showed that not only can this method be considered an alternative to SPE-LC–MS methods, but it is also more environmentally friendly due to its automation and solventless nature.