The use of multivariate statistics and mathematically modeled IR spectra for determination of HVO content in diesel blends

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22320%2F25%3A43929841" target="_blank" >RIV/60461373:22320/25:43929841 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0016236124021124?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0016236124021124?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.fuel.2024.132963" target="_blank" >10.1016/j.fuel.2024.132963</a>

Result language

angličtina

Original language name

The use of multivariate statistics and mathematically modeled IR spectra for determination of HVO content in diesel blends

Original language description

Diesel fuel containing one or more bio-components is currently increasingly represented on the market. The most common bio-component for diesel fuels is FAME (Fatty Acid Methyl Esters), but the share of diesel with HVO (Hydrotreated Vegetable Oil) content has been increasing in recent years. HVO has many advantages, compared to FAME, but the fact remains that it is difficult to detect and determine HVO in blends with mineral diesel fuel. The reason is the great similarity in the composition of HVO and mineral diesel fuel. A commonly used method for determining HVO content in diesel is radiocarbon C14 analysis, which can be performed by using LSC (Liquid Scintillation Counting) or AMS (Accelerator Mass Spectrometry). However, the important fact is that both methods are significantly expensive. For this reason, infrared spectrometry followed by chemometric data processing was used in this work. Infrared spectroscopy using ATR technique was utilized for primary data collection. Five PLS statistical models were prepared for the determination of HVO in blends with mineral diesel fuel. Analytical standards used in these models consisted of ten different mineral diesel fuels and five different HVO fuels. Spectra of these neat components were measured, spectra of calibration standards of blends were created mathematically by linear combination of the neat fuel components spectra (HVO and diesel). Two sets of validation standards which were applied in the first PLS model were created the same way as the calibration standards. The first model used only mathematically generated spectra for calibration and validation. Another four models were validated with real measured spectra, but they differed in the scope and method of calibration. All these five models were afterward optimized for minimalization of RMSEC (root mean square error of calibration) and RMSEP (root mean square error of prediction). Mean centering and other smoothing techniques were used for optimization. The RMSEP ranged from 1.67 to 2.22 vol% for models validated using the real spectra. For the mathematically validated model, it was less (0.32 vol% after optimization).

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20704 - Energy and fuels

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Fuel

ISSN

0016-2361

e-ISSN

1873-7153

Volume of the periodical

379

Issue of the periodical within the volume

January 2025

Country of publishing house

GB - UNITED KINGDOM

Number of pages

8

Pages from-to

132963

UT code for WoS article

001312388300001

EID of the result in the Scopus database

2-s2.0-85203403736