# Development and Optimization of a SPME-GC-FID Method for Ethanol Detection
## 1 Introduction
Summing up, several methodologies can be considered, each with its advantages and limitations:  
* Alternative Chromatographic Techniques: In addition to gas chromatography, liquid chromatography techniques, such as high-performance liquid chromatography (HPLC), could be explored. Each technique has its advantages, and the choice depends on factors such as sensitivity, selectivity, and the nature of the samples. On the other hand, liquid chromatography (LC) techniques, such as high-performance liquid chromatography (HPLC), may also be used for ethanol analysis. However, the choice between SPME-GC-FID and LC depends on the specific requirements of the analysis and the properties of the target analyte. Liquid chromatography generally excels in separating and analyzing a broader range of compounds, including those with higher molecular weights or polar characteristics. However, some studies reveal that for volatile compounds like ethanol, SPME-GC-FID often provides better sensitivity and faster analysis times [1; 2; 3; 4];
* Spectroscopic Techniques: Techniques like NIR, NMR, and MS could be considered for the direct detection of ethanol. These methods might provide alternative approaches with different detection sensitivities and specificities; however, studies reveal that the direct injection of ethanol in aqueous matrices reveals lower sensitivity [8; 9; 10; 11];
* Sensor Technologies: The use of sensors, such as electrochemical or optical sensors, could provide real-time detection and potentially offer advantages in terms of simplicity and rapidity. There are several available commercial sensors capable of transdermal monitoring of alcohol consumption using insensible sweat, such as the SCRAM(tm) and the WrisTAS(tm) biosensors. These sensors can provide information about days of abstinence, and even distinguish between heavy or sporadic alcohol ingestions. However, the reported devices have disadvantages, such as limited specificity and time delay after alcohol intake. Recent reports have demonstrated wearable alcohol biosensorscapable of greater specificity and near real-time monitoring through amperometric detection in sweat [18]. While we chose SPME injection gas chromatography for its specific advantages in our study, we acknowledge that alternative methodologies could provide valuable insights and complement our approach. Therefore, the choice of the solid-phase microextraction gas chromatography with flame ionization detection (SPME-GC-FID) method for ethanol detection in aqueous samples is supported by a combination of factors that collectively contribute to its suitability for the primary motivation of this work, which consists of detecting low ethanol concentrations in biological fluids for forensic purposes. Furthermore, this method can be used for future investigations in the fields of environmental analysis and the food and beverage industry. SPME allows for the selective preconcentration of volatile and semi-volatile compounds, including ethanol, from complex aqueous matrices [19]. The extraction phase of the SPME fiber, coated with a suitable material, facilitates the selective adsorption of the target analyte while minimizing interference from matrix components. Aqueous samples, such as water, sweat, and PBS, often contain a diverse range of compounds that can interfere with the accurate detection of ethanol. SPME serves to minimize matrix effects by selectively isolating ethanol, thus enhancing the method's specificity and reducing potential interferences. The flame ionization detector (FID) provides excellent sensitivity, a wide linear range, and low detection limits for compounds like ethanol since it operates based on the principle of detecting ions produced during the combustion of organic compounds. When a sample is introduced into the flame, it undergoes combustion in the presence of excess air (oxygen) [20]. The resulting ions and electrons contribute to the electrical current, which is then measured and correlated to the concentration of the analyte.