Hollow fiber liquid-phase microextraction coupled with gas chromatography-flame ionization detection for the profiling of fatty acids in vegetable oils

The development of a two phase hollow fiber liquid-phase microextraction technique, followed by gas-chromatography-flame ionization detection (GC-FID) for the profiling of the fatty acids (FAs) (lauric, myristic, palmitic, stearic, palmitoleic, oleic, linoleic, linolenic and arachidic) in vegetable oils is described. Heptadecanoic acid methyl ester was used as the internal standard. The FAs were transesterified to their corresponding methyl esters prior to the extraction. Extraction parameters such as type of extracting solvent, temperature, extraction time, stirring speed and salt addition were studied and optimized. Recommended conditions were extraction solvent, n-tridecane; extraction time, 35 min; extraction temperature, ambient; without addition of salt. Enrichment factors varying from 37 to 115 were achieved. Calibration curves for the nine FAs were well correlated (r(2)>0.994) within the range of 10-5000 μg L(-1). The limit of detection (signal:noise, 3) was 4.73-13.21 ng L(-1). The method was successfully applied to the profiling of the FAs in palm oils (crude, olein, kernel, and carotino cooking oil) and other vegetable oils (soybean, olive, coconut, rice bran and pumpkin). The encouraging enrichments achieved offer an interesting option for the profiling of the minor and major FAs in palm and other vegetable oils.     

Selecting a reduced suite of diagnostic ratios calculated between petroleum biomarkers and polycyclic aromatic hydrocarbons to characterize a set of crude oils

A set of 34 crude oils was analysed by GC-MS (SIM mode) and a suite of 28 diagnostic ratios (DR) calculated. They involved 18 ratios between biomarker molecules (hopanes, steranes, diasteranes and triaromatic steroids) and 10 quotients between polycyclic aromatic hydrocarbons. Three unsupervised pattern recognition techniques (i.e., principal components analysis, heatmap hierarchical cluster analysis and Kohonen neural networks) were employed to evaluate the final dataset and, thus, ascertain whether the crude oils grouped as a function of their geographical origin. In addition, an objective variable selection procedure based on Procrustes Rotation was undertaken to select a reduced set of DR that comprised for most of the information in the original data without loosing relevant information. A reduced set of four DR (namely; TA21, D2/P2, D3/P3 and B(a)F/4-Mpy) demonstrated to be sufficient to characterize the crude oils and the groups they formed.     

A surprising method for green extraction of essential oil from dry spices: Microwave dry-diffusion and gravity

Without adding any solvent or water, we proposed a novel and green approach for the extraction of secondary metabolites from dried plant materials. This "solvent, water and vapor free" approach based on a simple principle involves the application of microwave irradiation and earth gravity to extract the essential oil from dried caraway seeds. Microwave dry-diffusion and gravity (MDG) has been compared with a conventional technique, hydrodistillation (HD), for the extraction of essential oil from dried caraway seeds. Essential oils isolated by MDG were quantitatively (yield) and qualitatively (aromatic profile) similar to those obtained by HD, but MDG was better than HD in terms of rapidity (45min versus 300min), energy saving, and cleanliness. The present apparatus permits fast and efficient extraction, reduces waste, avoids water and solvent consumption, and allows substantial energy savings.     

Thorough evaluation of the validity of conventional enantio-gas chromatography in the analysis of volatile chiral compounds in mandarin essential oil: A comparative investigation with multidimensional gas chromatography

The present research is focused on the determination of the enantiomeric distribution of chiral compounds, contained in mandarin essential oils, by means of conventional chiral gas chromatography with flame ionization detection (enantio-GC-FID); the results attained were compared with those derived from heart-cutting multidimensional GC-mass spectrometry (MDGC/MS), to evaluate the reliability of the monodimensional technique as a tool for quality control. The Deans-switch MDGC system was equipped with two GC ovens, which were connected via a heated transfer line, a flame ionization detector (FID1) in the first dimension and a quadrupole MS as second-dimension detector. The a priori knowledge of potential co-elutions concerning target compounds (an enantiomer and an interfering compound), when using enantio-GC-FID, could enable the use of corrected enantiomer excess values. Correction factors could be calculated through a preliminary GC-FID analysis (using an apolar column), considering the peak areas of the known interferences. The method used for the calculation of a so-called “coelution correction factor” is described, along with some examples.     

冷凝法油气回收技术与应用

油品在储运和销售过程中部分轻烃组分挥发进入大气,造成资源浪费和环境危害.油气回收既可实现油气污染治理又能产生可观的经济效益.结合中国油气储运和销售环节的现状以及相关技术的发展,对几种油气回收的方法进行了对比分析,认为采用多元工质复叠(或自复叠)制冷技术的冷凝法具有较好的经济性和可靠性.介绍了自主研发的冷凝式油气回收设备...     

常见园林植物对NO2胁迫的耐受性及吸收与恢复能力

【目的】以城市道路绿化实际应用为依据,研究江苏省境内常见的园林植物对NO₂胁迫的耐受性及吸收能力和恢复能力。【方法】采用实验室人工熏气方法,分析江苏省常见的38种园林植物对NO₂的耐受性及吸收与恢复能力,筛选耐受性强、吸收能力强和恢复能力强的植物种类。【结果】对NO₂耐受性强且吸收能力强或较强的植物有熊掌木(×Fatshedera lizei)、龟甲冬青(Ilex crenata var. convexa)、木姜子(Litsea pungens)、常春藤(Hedera nepalensis)、金边黄杨(Euonymus japonicus ‘Aurea-marginatus’)、小叶黄杨(Buxus sinica var. parvifolia)、大吴风草(Farfugium japonicum);对NO₂耐受性强且恢复能力强或较强的植物包括普陀鹅耳枥(Carpinus putoensis)、熊掌木、海桐(Pittosporum tobira)、龟甲冬青、瓜子黄杨(Buxus sinica)、木姜子、金叶银杏(Ginkgo biloba ‘Wannianjin’)、金边黄杨、矮麦冬(Ophiopogon japonicus ‘Nana’)和金边玉簪(Hosta ‘Green Gold’)等19个种;吸收能力和恢复能力均强或较强水平的植物有茶梅(Camellia sasanqua)、金边黄杨、常春藤、花叶蔓长春(Vinca major ‘Variegata’)、小叶黄杨、大吴风草和鸢尾(Iris tectorum)等;对NO₂耐受且吸收能力和恢复能力均强或较强的植物有金边黄杨、常春藤、木姜子、熊掌木、龟甲冬青、小叶黄杨和大吴风草。【结论】在分析近6年南京市城区道路NO₂等污染物基础上,认为 NO₂是南京道路交通区域主要污染物。本研究筛选出对NO₂耐受性、吸收和恢复能力强的植物种类补充和完善了传统文献中抗NO₂胁迫的园林植物名录,可为NO₂污染区及潜在污染区道路绿化树种的选择和配置提供一定的理论依据。     

考虑能耗优化的多目标原油短期调度问题研究

针对在原油管道运输过程中的能耗优化问题,该文提出了一个以最小化管道转运能耗、供油罐使用个数、蒸馏塔使用供油罐的切换次数、原油在供油罐和管道中的混合成本为目的的多目标优化模型.然后,针对原油短期调度问题的特点,提出了一种改进的交叉和变异算子.最后,该文对比分析了8种综合性能较好的多目标进化算法.实验结果表明:NSGA-III算法在求解该问题时的性能较优.与现有研究对比,该算法在减少调度过程中的能耗和原油混合成本方面具有显著效果.     

水面油污染物差分偏振光谱信号预处理算法研究

采用差分偏振光谱法在3～5μm波段对水面溢油污染物进行被动遥感时,所测差分偏振光谱是含有强大气吸收光谱信号与油污染物目标弱光谱信号的混合谱,这给油污染物光谱特征识别带来了困难。另外,受环境因素以及油膜自身张力影响,水面油膜厚度分布以及油膜表面粗糙度在测量过程中发生变化,从而使得连续测量的差分偏振光谱中油污染物光谱信息含量存在不同。利用这一特点,基于固定点迭代的快速主成分分析算法FastPCA设计了水面溢油污染物差分偏振光谱信号预处理算法。实验结果表明,该算法可以有效地将水面油污染物目标光谱特征信息从具有强大气吸收的混合差分偏振光谱信号中提取出来,通过光谱重构得到油污染物光谱特征信号,可用于进一步的定性、定量分析。     

R600a／矿物冷冻油混合物表面张力

本文利用新改进的表面张力实验系统对R600a／矿物冷冻油混合物的表面张力进行了实验研究,其中R600a的质量分数分别为O．95、0．90和0．85,温度范围为253．15-333．15K。实验结果表明,随着含油量的增加,R600a／矿物冷冻油的表面张力逐渐减小,矿物油的存在对纯质制冷剂的表面张力有比较明显的影响。     

Forecasting the volatility of crude oil futures using intraday data

We use the information in intraday data to forecast the volatility of crude oil at a horizon of 1–66 days using a variety of models relying on the decomposition of realized variance in its positive or negative (semivariances) part and its continuous or discontinuous part (jumps). We show the importance of these decompositions in predictive (in-sample) regressions using a number of specifications. Nevertheless, an important empirical finding comes from an out-of-sample analysis which unambiguously shows the limited interest of considering these components. Overall, our results indicates that a simple autoregressive specification mimicking long memory and using past realized variances as predictors does not perform significantly worse than more sophisticated models which include the various components of realized variance.