Research and Teaching Group in Environmental Toxicology and Risk Assessment (TAyER), Rey Juan Carlos University, 28933, Móstoles, Madrid, Spain; Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada.
Research and Teaching Group in Environmental Toxicology and Risk Assessment (TAyER), Rey Juan Carlos University, 28933, Móstoles, Madrid, Spain; Seguridad y Bienestar Animal, S.L., Barcelona, Spain.
Sci Total Environ. 2018 Jan 15;612:1058-1071. doi: 10.1016/j.scitotenv.2017.08.066. Epub 2017 Sep 7.
This study presents one of the most complete applications of probabilistic methodologies to the risk assessment of emerging contaminants. Perhaps the most data-rich of these compounds, caffeine, as well as its main metabolite (paraxanthine), were selected for this study. Information for a total of 29,132 individual caffeine and 7442 paraxanthine samples was compiled, including samples where the compounds were not detected. The inclusion of non-detect samples (as censored data) in the estimation of environmental exposure distributions (EEDs) allowed for a realistic characterization of the global presence of these compounds in aquatic systems. EEDs were compared to species sensitivity distributions (SSDs), when possible, in order to calculate joint probability curves (JPCs) to describe the risk to aquatic organisms. This way, it was determined that unacceptable environmental risk (defined as 5% of the species being potentially exposed to concentrations able to cause effects in>5% of the cases) could be expected from chronic exposure to caffeine from effluent (28.4% of the cases), surface water (6.7% of the cases) and estuary water (5.4% of the cases). Probability of exceedance of acute predicted no-effect concentrations (PNECs) for paraxanthine were higher than 5% for all assessed matrices except for drinking water and ground water, however no experimental effects data was available for paraxanthine, resulting in a precautionary deterministic hazard assessment for this compound. Given the chemical similarities between both compounds, real effect thresholds, and thus risk, for paraxanthine, would be expected to be close to those observed for caffeine. Negligible Human health risk from exposure to caffeine via drinking or groundwater is expected from the compiled data.
本研究是将概率方法应用于新兴污染物风险评估的最完整的研究之一。在本研究中，选择了其中数据最丰富的两种化合物：咖啡因及其主要代谢物（1,7-二甲基黄嘌呤）。共收集了 29132 份咖啡因和 7442 份 1,7-二甲基黄嘌呤的个体样本，包括未检出化合物的样本。在估计环境暴露分布（EED）时，包含未检出样本（作为删失数据）可以真实地描述这些化合物在水生系统中的全球存在情况。当可能时，将 EED 与物种敏感性分布（SSD）进行比较，以计算联合概率曲线（JPC）来描述水生生物的风险。通过这种方式，确定从废水中（28.4%的情况下）、地表水（6.7%的情况下）和河口水中（5.4%的情况下）的慢性暴露中，可能会导致不可接受的环境风险（定义为 5%的物种可能暴露在能够引起 5%以上情况的浓度下）。除了饮用水和地下水外，对于所有评估的基质，1,7-二甲基黄嘌呤的急性预测无效应浓度（PNEC）超过 5%的概率都高于 5%，但是对于 1,7-二甲基黄嘌呤，没有实验效应数据，因此对该化合物进行了预防性的确定性危害评估。鉴于这两种化合物具有化学相似性，因此 1,7-二甲基黄嘌呤的实际效应阈值和风险预计会接近咖啡因的观察结果。从已编译的数据来看，通过饮用或地下水暴露于咖啡因对人类健康的风险可以忽略不计。
