Eiroa A A, Blanco E V, Mahía P L, Lorenzo S M, Rodríguez D P, Fernández E F
A Coruña University, Department of Analytical Chemistry, A Zapateira, Spain.
J AOAC Int. 2000 Jul-Aug;83(4):977-83.
The most suitable wavelength intervals were selected for the determination of 4 polycyclic aromatic hydrocarbons (PAHs; benzo[g,h,i]perylene, dibenzo[a,h]anthracene, pyrene, and triphenylene) in very complex mixtures of 11 PAHs: anthracene, benz[a]anthracene, benzo[a]pyrene, benzo[b]fluoranthene, benzo[g,h,i]perylene, benzo[k]fluoranthene, chrysene, dibenz[a,h]anthracene, phenanthrene, pyrene, and triphenylene. The multiple linear regression algorithm was applied to measurements made in several wavelength intervals previously selected on the basis of sensitivity and minimum number of interfering compounds. Of the different models obtained, those displaying minimum error propagation in the analytical result were selected. By applying the models proposed in this study, we precisely and accurately determined benzo[g,h,i]perylene, dibenz[a,h]anthracene, pyrene, and triphenylene in complex mixtures--a feat that could not be achieved by the use of constant-wavelength spectrofluorimetry in combination with second-derivative techniques.
在由11种多环芳烃（PAHs）组成的非常复杂的混合物中：蒽、苯并[a]蒽、苯并[a]芘、苯并[b]荧蒽、苯并[g,h,i]苝、苯并[k]荧蒽、 Chrysene、二苯并[a,h]蒽、菲、芘和三亚苯，选择了最合适的波长区间来测定4种多环芳烃（PAHs；苯并[g,h,i]苝、二苯并[a,h]蒽、芘和三亚苯）。将多元线性回归算法应用于在先前基于灵敏度和干扰化合物的最少数量选择的几个波长区间内进行的测量。在获得的不同模型中，选择了在分析结果中显示最小误差传播的模型。通过应用本研究中提出的模型，我们精确且准确地测定了复杂混合物中的苯并[g,h,i]苝、二苯并[a,h]蒽、芘和三亚苯——这是通过使用恒波长荧光光谱法结合二阶导数技术无法实现的壮举。
Zotero 插件