Geological Survey of Canada, Natural Resources Canada, Québec City, Québec G1K 9A9, Canada.
INRS Eau Terre Environnement, Québec City, Québec G1K 9A9, Canada.
Environ Sci Technol. 2020 Mar 3;54(5):2790-2799. doi: 10.1021/acs.est.9b06875. Epub 2020 Feb 17.
Distinguishing between naphthenic acids (NAs) associated with oil sands process-affected water (OSPW) and those found naturally in groundwaters in contact with the bituminous McMurray Formation poses a considerable analytical challenge to environmental research in Canada's oil sands region. Previous work addressing this problem combined high-resolution Orbitrap mass spectrometry with carbon isotope values generated by online pyrolysis (δC) to characterize and quantify the acid extractable organics (AEOs) fraction containing NAs in the subsurface near an oil sands tailings pond. Here, we build upon this work through further development and application of these techniques at two different study sites near two different tailings ponds, in conjunction with the use of an additional isotopic tool-sulfur isotope analysis (δS) of AEOs. The combined use of both δC and δS allowed for discrimination of AEOs into the three end-members relevant to ascertaining the NA environmental footprint within the region: (1) OSPW; (2) McMurray Formation groundwater (i.e., naturally occurring bitumen), and; (3) naturally occurring non-bitumen. A Bayesian isotopic mixing model was used to determine the relative proportions of these three sources in groundwater at both study sites. Although background levels of OSPW-derived AEOs were generally low, one sample containing 49-99% (95% credibility interval) OSPW-derived AEOs was detected within an inferred preferential flow-path, highlighting the potential for this technique to track tailings pond seepage.
区分与油砂加工影响水(OSPW)相关的环烷酸(NA)和那些在与沥青质麦克默里组接触的地下水中自然存在的环烷酸,这对加拿大油砂地区的环境研究构成了相当大的分析挑战。以前的工作结合了高分辨率轨道阱质谱和在线热解产生的碳同位素值(δC),以对油砂尾矿池附近地下水中含有 NA 的可酸提取有机物(AEOs)部分进行特征描述和量化。在这里,我们通过在两个不同的尾矿池附近的两个不同研究地点进一步开发和应用这些技术,并结合使用另外一种同位素工具——AEOs 的硫同位素分析(δS),在此基础上进行了扩展。联合使用 δC 和 δS 可以将 AEOs 分为三个与确定该地区 NA 环境足迹相关的端元:(1)OSPW;(2)麦克默里组地下水(即天然存在的沥青);(3)天然存在的非沥青。贝叶斯同位素混合模型用于确定两个研究地点地下水中这三个来源的相对比例。尽管 OSPW 衍生的 AEOs 的背景水平通常较低,但在一个推断的优先流路径内检测到一个含有 49-99%(95%置信区间)OSPW 衍生的 AEOs 的样本,突出了该技术跟踪尾矿池渗漏的潜力。