Source Allocation by Least-Squares Hydrocarbon Fingerprint Matching

There has been much controversy regarding the origins
of the natural polycyclic aromatic hydrocarbon (PAH) and
chemical biomarker background in Prince William Sound
(PWS), Alaska, site of the 1989 Exxon Valdez oil spill. Different
authors have attributed the sources to various proportions
of coal, natural seep oil, shales, and stream sediments.
The different probable bioavailabilities of hydrocarbons from
these various sources can affect environmental damage
assessments from the spill. This study compares two different
approaches to source apportionment with the same data
(136 PAHs and biomarkers) and investigate whether increasing
the number of coal source samples from one to six
increases coal attributions. The constrained least-squares
(CLS) source allocation method that fits concentrations
meets geologic and chemical constraints better than partial
least-squares (PLS) which predicts variance. The field
data set was expanded to include coal samples reported
by others, and CLS fits confirm earlier findings of low coal
contributions to PWS.

关于阿拉斯加威廉王子湾（PWS，1989年埃克森·瓦尔迪兹号油溢事故发生地）的天然多环芳烃（PAH）与化学生物标志物本底值的来源问题，长期存在诸多争议。不同学者将其来源归因于煤、天然渗漏石油、页岩与河流沉积物的不同比例组合。上述各类来源的烃类物质生物可利用性存在显著差异，这会影响油溢事故后的环境损害评估。本研究采用同一套数据集（涵盖136种PAH与生物标志物）对比两种不同的源解析方法，并探究将煤源样本数量从1份增至6份是否会提升煤来源的归因占比。相较于预测方差的偏最小二乘法（PLS），拟合浓度的约束最小二乘法（CLS）更符合地质与化学约束条件。本研究拓展了野外数据集，纳入了其他学者报道的煤源样本，CLS拟合结果验证了此前的结论：威廉王子湾的煤源贡献占比极低。