OPTIMIZATION OF GC-MS DERIVATIZATION FOR PFAS DETECTION IN WATER: ENHANCING SUSTAINABILITY WITH COST-EFFECTIVE TECHNOLOGY

Per- and polyfluoroalkyl substances (PFAS) encompass organic molecules with fluorinated hydrophobic carbon chains linked to various hydrophilic functional groups. Used in over 200 sectors, from industrial mining to food production and firefighting foams, PFAS are assessed for their chemical and thermal stability and ability to repel oil and water. However, PFAS degrades slowly in the environment, earning them the label “forever chemicals,” which poses significant sustainability challenges regarding environmental health. Detection in natural systems is still relatively unexplored. While liquid chromatography-mass spectrometry (LC-MS) has been the preferred PFAS detection method over the last two decades, gas chromatography-mass spectrometry (GC-MS) remains underutilized despite its cost-effectiveness and high resolution. This study optimizes a method for detecting perfluorooctanoic acid (PFOA), a PFAS compound, in water samples using GC-MS derivatization. Using different derivatizing agents, we generated a linearity plot correlating mass spectrometry signal with PFOA concentrations ranging from 1–1000 ng/mL, utilizing 8860 GC and 5977B MS (Agilent Technologies®). This approach enhances detection efficiency and supports sustainable practices by leveraging cost-effective, widely available GC-MS technology.