Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States.
Environ Sci Technol. 2011 Jan 15;45(2):468-73. doi: 10.1021/es1030068. Epub 2010 Dec 8.
Modeling of human exposure to aqueous algal odorants geosmin (earthy), 2-methylisoborneol (musty), and (trans,cis)-2,6-nonadienal (cucumber, fishy), and the solvent trichloroethylene (sweet chemical), was investigated to improve the understanding of water-air transfer by including humans as sensors to detect contaminants. A mass-transfer model was employed to determine indoor air concentrations when water was used for showering under varying conditions (shower stall volume, water and air flow rate, temperature, aqueous odorant concentration, shower duration). Statistical application of multiple linear regression and tree regression were employed to determine critical model parameters. The model predicted that concentrations detectable to the human senses were controlled by temperature, odor threshold, and aqueous concentration for the steady-state model, whereas shower volume, air flow, and water flow are also important for the dynamic model and initial detection of the odorant immediately after the showering is started. There was excellent agreement of model predictions with literature data for human perception of algal odorants in their homes and complaints to water utilities. TCE performed differently than the algal odorants due to its higher Henry's law constant, in spite of similar gas and liquid diffusivities. The use of nontoxic odorants offers an efficient tool to calibrate indoor air/water shower models.
人体暴露于水生藻类气味物质（土腥味）、2-甲基异冰片（霉味）、（顺式，反式）-2,6-壬二烯醛（黄瓜味，鱼腥味）和溶剂三氯乙烯（甜味化学物质）的模型研究旨在通过将人类作为传感器来检测污染物，以提高对水-气转移的理解。采用质量传递模型来确定在不同条件下（淋浴间体积、水和空气流速、温度、水气味浓度、淋浴时间）使用水淋浴时室内空气浓度。采用多元线性回归和树回归的统计应用来确定关键模型参数。该模型预测，对于稳态模型，人类可感知的浓度受温度、气味阈值和水浓度控制，而对于动态模型和淋浴开始后立即对气味的初始检测，淋浴体积、空气流量和水流也很重要。模型对人类在家中感知藻类气味物质和向供水公司投诉的预测与文献数据具有极好的一致性。尽管 TCE 的气体和液体扩散系数相似，但由于亨利定律常数较高，其表现与藻类气味物质不同。使用无毒气味物质为校准室内空气/水淋浴模型提供了有效的工具。
