MONITORING OF ADULTERANTS IN CRAMBE METHYL BIODIESEL IN MIXTURES WITH DIESEL, USING FT-MIR AND MULTIVARIATE CONTROL CHARTS BASED ON NET ANALYTE SIGNAL

Adulterants in biodiesel/diesel blends modifies its physical and chemical properties. In this work, Fourier Transform Mid-Infrared spectrometry (FT-MIR) and multivariate control charts based on Net Analyte Signal (NAS) were used to monitor the quality of Crambe methyl biodiesel in relation to the biodiesel content and the presence of adulterants. The calibration model was constructed from the decomposition of the instrumental signals of the calibration samples into three vectors: NAS, interference and residual. From these vectors, three control charts were built: (i) NAS chart to monitor the analyte of interest (Crambe methyl biodiesel); (ii) Interference chart to monitor the data matrix (all components in diesel without the analyte of interest); and (iii) Residual chart to monitor any non-systematic variations. To validate the calibration model, other groups of B10, BX and B10 samples adulterated by direct addition of soybean oil and used fry oil in the range of 4.85-30.13% (v/v) were used. All samples prepared in-quality specifics were correctly classified as “in-quality control” samples, and other samples were correctly classified as “out-of-quality control” samples. Therefore, the methodology developed proved to be efficient in monitoring the quality of this fuel and it can be used by supervisory and quality control agencies.

生物柴油与柴油混合燃料中的掺假物质会改变其物理及化学特性。本研究采用傅里叶变换中红外光谱法（Fourier Transform Mid-Infrared spectrometry, FT-MIR）与基于净分析物信号（Net Analyte Signal, NAS）的多变量控制图，针对海甘蓝甲酯生物柴油在混合燃料中的占比及掺假物的存在情况，对该混合燃料的品质开展监测。该校准模型通过将校正样品的仪器信号分解为三类矢量——净分析物信号、干扰信号与残差信号——构建而成。基于上述三类矢量，研究人员搭建了三种控制图：(i) 净分析物信号控制图，用于监测目标分析物（海甘蓝甲酯生物柴油）；(ii) 干扰控制图，用于监测数据矩阵（柴油中除目标分析物外的所有组分）；(iii) 残差控制图，用于监测所有非系统性变化。为验证该校准模型，本研究采用了多组经直接添加大豆油与煎炸废油掺假的B10、BX及B10样品，掺假比例范围为4.85%~30.13%（体积比）。所有符合质量规范的制备样品均被正确归类为"质量受控"样品，其余样品则被正确归类为"质量失控"样品。因此，本研究开发的方法在该燃料的品质监测中展现出优异效能，可被监管机构与质量控制部门采用。