Benzene in Gasoline

Benzene is a naturally occurring compound in crude oil and a very useful chemical solvent and feedstock. Unfortunately, it can be a significant health risk and is therefore environmentally regulated in many common products especially gasoline. Strict limits are put on the concentration and accurate measurements are required. The traditional analytical method for measuring benzene is gas chromatography (GC), which is time and labor intensive. This note will discuss the use of our hardware and software tools for the measurement of % Benzene in fuel products using fiber optic based, Near-Infrared (NIR) spectroscopy. NIR can be applied in real time directly in process monitoring or as a laboratory procedure. In either case NIR is a time and money saving alternative to traditional methods.

Figure 1: NIR Specta of Pure Benzene and Gasoline Samples

The spectra and concentration data were submitted to the third party software, and a calibration model was developed using PLS regression methodology. For a discussion of PLS and other multivariate calibration techniques see Martens and Naes 1 and ASTM E16552.

Results – Prediction of Benzene Concentrations

The model was used to predict benzene concentrations using an in-situ probe inserted in a process stream measuring in real time. The results for this are shown in Figure 2 as a scatter plot and in Figure 3 as a trend plot. The model produced a prediction RMSEP (root mean square error of prediction) of 0.30% benzene. This is in good agreement with the accuracy of the standard laboratory method.

Conclusion

The measurement of benzene in gasoline using NIR spectroscopy is both fast and reliable utilizing the our hardware and software tools as described here. This method minimizes the need for laboratory sample collection. Results are available in real-time (seconds) for multiple parameters in complex streams. For more detailed information regarding system specifications please contact a Process Insights sales or technical specialist.

Application Note

References

H. Martens, T. Naes, Multivariate Calibration, John Wiley & Sons, 1989.
ASTM E1655 Standard Practices for Infrared, Multivariate, Quantitative Analysis.