## 4 Conclusions  
We have shown that a conceptually simple THz-TDS time-of-flight method relying on a straightforward THz pulse delay measurement can be successfully used to detect very small, on an order of parts-per-million of mass fraction, concentrations of water (H\({}_{2}\)O) or isopropanol (C\({}_{3}\)H\({}_{8}\)O) in quasi-binary gasoline solutions. The most important prerequisite for such sensitive detection is the stable time performance of a spectrometer and the femtosecond precision of the THz pulse time delay measurement.  
The method is calibration-free, and ab initio calculations of the pulse delays resulting from its interaction with gasoline mixtures were possible, provided that a satisfactory model of the refractive index of a solution is known. We have found that this requirement is much better fulfilled for isopropanol-gasoline mixtures than for water-gasoline mixtures and attributed this fact to the good solubility of isopropanol in gasoline due to its alkyl group.  
A modified model of the Gladstone-Dale mixing rule was used to represent the refractive index of gasoline mixtures. According to this model, the linear relation between the THz pulse propagation time and admixture mass fraction in a solution was found. This linear relation was qualitatively confirmed in the measurements. However, the quantitative agreement was found to be sufficiently satisfactory only in the case of isopropanol samples.  
Based on the empirically measured linear relations between the pulse time of flight through the mixture and the mass fraction of water or isopropanol, we have determined the detection limits of these substances to be 250 ppm and 125 ppm, respectively. These determined limits of sensitivity values are approaching those obtained with the use of much more complicated and time-consuming spectroscopic methods (like spectroscopy of the evaporated gasoline gas phase).  
Therefore, our work clearly shows that the pulse time delay measurement by THz-TDS is a sensitive and fast method of gasoline contamination detection and, as such, can be easily integrated with industrial online real-time quality control applications.  
Conceptualization, K.S.; methodology, K.S. and E.K.-M.; software, K.S.; validation, K.S. and E.K.-M.; formal analysis, K.S.; investigation, K.S. and E.K.-M.; resources, T.S., and W.K. data curation, K.S. and E.K.-M.; writing--original draft preparation, K.S. and E.K.-M.; writing review and editing, K.S., E.K.-M., and V.M., T.S. and W.K.; visualization, K.S.; funding acquisition, T.S., G.C. and W.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the \"International Research Agendas\" program of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund (No. MAB/2018/9) for CENTERA.  
Not applicable.  
We would like to thank [PERSON] for his technical assistance and PKN Orlen S. A. representatives for fruitful discussions.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.