###### Abstract  
Methanol gasoline blends are a more economical, and environmentally friendly fuels than gasoline alone, and are widely used in the transportation industry. The content of methanol in methanol gasoline plays an important role in ensuring the quality of gasoline. In some solutions, due to the shortage of energy and illegal profits, the problem of gasoline adulteration and its fineness, has received more and more attention, which would seriously affect the operating condition and service life of internal combustion engines. Therefore, it is very important to identify the correct level of gasoline. However, the traditional detection method is complex and time-consuming. To this end, the feasibility of using attenuated total reflectance Fourier transform infrared (ATR-FTIR) methods coupled with chemometrics methods were investigated to quantitatively and qualitatively analyze methanol gasoline. The qualitative analysis result of partial least squares discriminant analysis (PLS-DA) obtained 100% and 98.66% accuracy in the calibration set and the prediction set, respectively. As for quantitative analysis; two regression algorithms of partial least squares regression (PLSR) and the least square support vector machine (LS-SVM), as well as two variables selection methods of the successive projections algorithm (UVE) competitive adaptive reweighted sampling (CARS) and uninformative variable elimination (UVE) were combined to establish the quantitative model. By comparing the performance of the optimal models; the UVE-PLSR model performed best with a residual predictive deviation (RPD) value of 6.420. The qualitative and quantitative analysis results demonstrate the feasibility of using ATR-FTIR spectra to detect the methanol in methanol gasoline. It is believed that the promising IR spectra will be widely used in gasoline energy quality control in the further. methods: general - methods  
transportation industry has led to a reduction in non-renewable oil resources and the increasingly serious atmospheric pollution problem [2]. To address this issue, it is necessary to find an environmentally, friendly, and economically viable alternative resource. Methanol gasoline as an excellent alternative fuel for engines, which has advantages such as high octane number, and good resistance to violent and clean burning [3]. Due to these excellent qualities and appropriate economic suitability, methanol gasoline can play an important role in addressing the issue of energy shortage and environmental pollution. Thus, it has been widely used in transportation, including motor vehicles and internal combustion engines [4]. According to the reports of the relevant literature, the adding ratio of methanol in methanol gasoline varies from 0%-80% [5] since methanol gasoline can be prepared by directly mixing gasoline and methanol. In addition, this provides an opportunity for some unscrupulous traders to sell high-methanol gasoline at a low methanol content of gasoline to earn illegal profits. Therefore, it is necessary to develop an accurate and rapid method to qualitatively and quantitatively analyze the methanol content in methanol gasoline. There are numerous detection methods for determining methanol content in gasoline and the commonly used is gas chromatography (GC) or gas chromatography-mass spectrometer (GC-MS) [6]. Although these detection methods have high sensitivity and accuracy, they are time-consuming and complex, require toxic and hazardous reagents, and cannot meet the needs of online monitoring. The development and application of infrared (IR) spectroscopy technology provides a novel opportunity for rapid detection of methanol content in methanol gasoline [6]. As a rapid and non-destruction detection technology, IR spectroscopy technology has been applied in various subject fields, such as chemistry, agriculture, food quality and the environment. Moreover, there are several studies using near infrared spectra to analyze gasoline products and obtain good qualitative and quantitative detection results [6; 7; 8; 9].