1.广州海关技术中心,广东 广州 510623
2.中国科学院广州能源研究所,广东 广州 510640
肖 前,硕士,研究员,研究方向:再生资源环境风险识别与碳排放评估研究,E-mail:xiaq@iqtcnet.cn
收稿:2026-07-16,
修回:2026-08-13,
录用:2026-08-20,
网络首发:2026-09-01,
纸质出版:2026-10-15
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夏莹,段逸品,张子豪,蔡国田,肖前.基于逐步回归的生物航煤属性鉴别[J].分析测试学报,2026,45(10):2171-2178.
XIA Ying,DUAN Yi-pin,ZHANG Zi-hao,CAI Guo-tian,XIAO Qian.Attribute Identification of Bio-aviation Jet Fuel via Stepwise Regression[J].Journal of Instrumental Analysis,2026,45(10):2171-2178.
夏莹,段逸品,张子豪,蔡国田,肖前.基于逐步回归的生物航煤属性鉴别[J].分析测试学报,2026,45(10):2171-2178. DOI: 10.12452/j.fxcsxb.26071601.
XIA Ying,DUAN Yi-pin,ZHANG Zi-hao,CAI Guo-tian,XIAO Qian.Attribute Identification of Bio-aviation Jet Fuel via Stepwise Regression[J].Journal of Instrumental Analysis,2026,45(10):2171-2178. DOI: 10.12452/j.fxcsxb.26071601.
针对现行航空喷气燃料标准仅规定常规指标,无法鉴别来源(石油基、生物基或混合),存在监管盲区的实际情况,该文提出逐级鉴别策略(主要成分初筛-理化性质定性-生物基碳含量确证),有效鉴别出酯和脂肪酸加氢改质工艺生产的生物航煤(HEFA-SPK)的属性鉴别。首先,基于气相色谱-质谱(GC-MS)分析,排除碳数分布不在C6~C17的燃料;其次依据密度及芳烃含量快速定性,辅以馏程、闪点综合评判;最后以生物基碳含量确证,高于97.0%时判定为纯生物基燃料,低于0.5%时认定为石油基燃料。掺混比例在1%~30%范围时,采用逐步回归构建基于闪点、馏程宽度及生物基碳含量的掺混比例预测模型,并经配对
t
检验验证。结果表明,模型可准确预测HEFA-SPK掺混比例(
R
²
>
0.99),为生物航煤监管与来源识别提供技术支撑。
Current aviation jet fuel specifications only prescribe basic technical indicators,thus creating a regulatory gap because they cannot effectively distinguish between conventional petroleum-derived sources,bio‑based sources,or their blends. To address this issue,a stepwise identification strategy comprising component screening,rapid physicochemical qualitative analysis,and bio-based carbon content confirmation is proposed for the attribute identification of hydroprocessed esters and fatty acids synthetic paraffinic kerosene (HEFA-SPK). First,gas chromatography-mass spectrometry is performed to screen the carbon number distribution;samples outside the typical avia
tion fuel range (C6-C17) are excluded. Subsequently,rapid qualitative discrimination is achieved based on density and aromatic content,supplemented by distillation range and flash point as auxiliary parameters for a comprehensive evaluation. Finally,bio-based carbon content serves as the key evidence:a measured content above 97.0% identifies HEFA-SPK,while a value below 0.5% indicates petroleum-based jet fuel. For intermediate blending ratios (1%-30%),a stepwise regression approach is employed to develop a predictive model for the blending ratio of bio-based fuel,and the model is validated via a paired
t
-test. Results show that the linear regression model based on flash point,distillation range,and biogenic carbon content accurately predicts the blending ratio (
R
²
>
0.99),thus providing reliable technical support for the quality supervision and source identification of bio-based aviation fuel.
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