The Analysis of Electronic Cigarette E Liquids by GC-MS

Significance of the Topic

Electronic cigarettes have surged in popularity, with over 35 million users worldwide and a market exceeding £17 billion. Despite widespread use, the detailed composition of e-liquids—particularly flavorings and impurities—remains undercharacterized. As vaping regulations evolve, comprehensive analytical methods are essential to ensure product safety, label accuracy, and regulatory compliance.

Goals and Study Overview

This study aims to develop a rapid, robust gas chromatography–mass spectrometry (GC-MS) method for

• Quantifying nicotine content in e-liquids
• Profiling base ingredients
• Identifying flavor compounds and potential impurities
• Applying the method to four commercial e-liquid flavors: bubble-gum, pear drop, cherry tree, and blueberry

Applied Instrumentation

• Gas chromatograph: Scion 436 GC
• Mass spectrometer: Scion Single Quadrupole (SQ) MS
• Autosampler: 8400 Autosampler
• Column: Scion-5MS (30 m × 0.25 mm × 1.0 µm)
• Software: Mass Spec Work Station with NIST spectral library

Methodology

E-liquids were analyzed neat and following 1:2 dilution in methanol. Injection parameters included split injection (1:10), 0.1 µL volume, and an oven program ramping from 40 °C to 220 °C. Helium carrier gas at 1 mL/min was used. A full-scan approach (45–500 amu) was enhanced by dividing acquisition into three scan segments (0.5–8 min, 9.75–14 min, 18–28 min) to mitigate propylene glycol and glycerin overloading. Nicotine calibration standards (0.5, 1, 3, 5, 10 mg) enabled quantification.

Main Results and Discussion

• Neat injections exhibited overloading of matrix components (propylene glycol, glycerin), obscuring minor peaks
• Sample dilution and segmented scanning resolved previously masked flavor and impurity peaks without complex preparation
• All samples contained labeled base ingredients; additionally, 36 flavor-related compounds and impurities were detected
• Common additives included glycerin diacetate, vanillin, ethyl vanillin, and γ-decalactone; isoamyl acetate appeared in three flavors; piperonal was unique to cherry tree
• NIST library matching confirmed component identities
• Nicotine quantification was linear (R² > 0.99), with measured levels within ±7% of label claims; the blueberry sample matched exactly

Benefits and Practical Applications

This GC-MS approach offers:

• Rapid, comprehensive compositional profiling of e-liquids
• Accurate nicotine quantification for quality assurance
• Detection of regulated and unregulated impurities
• Reduced sample preparation and data processing time

Future Trends and Potential Applications

Potential developments include:

• Extension of spectral libraries for emerging flavor agents
• Integration with high-resolution mass spectrometry for trace impurity analysis
• Automation and advanced data analytics for routine quality monitoring
• Standardization of testing protocols to support regulatory frameworks

Conclusion

The scan-segment GC-MS method on the Scion 436 platform enables fast, reliable analysis of e-liquids, offering precise nicotine measurement and broad detection of flavor compounds and impurities with minimal sample handling, supporting industry and regulatory requirements for safety and labeling accuracy.