Analytical Method for Determining Renewable Diesel and Identifying Feedstock in Fossil Diesel Blends Using δ¹³C for Fuel Traceability

Renewable diesel is an innovative fuel derived from renewable feedstocks (vegetable oils and frying oils) mainly via hydrodeoxygenation, yielding hydrocarbons chemically similar to fossil diesel. Its use reduces greenhouse gas emissions, decreases dependence on fossil fuels, and is compatible with conventional engines. However, ensuring authenticity is essential to prevent adulteration. This study proposes an analytical method using δ13C to differentiate renewable diesel from fossil diesel. Renewable diesel exhibited δ13C values ranging from −30.8‰ (soybean) to −28.1‰ (macauba), indicating its renewable origin. Fossil diesel showed δ13C values around −25‰, enabling a clear distinction. A calibration curve using soybean-based renewable diesel blends with fossil diesel showed linear range of 10 to 100%v/v, described by the equation (C = −0.06RD −24.7; r = 0.999). The approach achieved detection and quantification limits of 3.3%v/v and 10.0%v/v, respectively, and coefficient of variation of 1.5% (n = 10), representing the lowest renewable diesel content in fossil diesel blends that can be reliably detected and accurately quantified for regulatory compliance. Matrix-matched calibration yield recoveries of 93–120% and 71–99% with 10 and 50%v/v renewable diesel, respectively. Mixtures of fossil diesel and renewable diesel (1–3% v/v), from soybean oil and used frying oil, were classified using hierarchical and K-means clustering. Clustering by renewable diesel content showed distances of 12–24, within-cluster sum of squares (WCSS) = 143, intracluster distance = 3; clustering by feedstock showed distances of 2.0–2.5, WCSS = 82.7, intracluster distance = 1.4. ANOVA confirmed significant group differences (F = 12.82; p = 0.0339). The method is robust and effective for monitoring the authenticity and detecting low-level of renewable diesel in blends with fossil diesel.