Sensitivity of key factors and uncertainties in health risk assessment of
benzene pollutant |
| |
Authors: | LIU Zhi-quan ZHANG Ying-hu LI Guang-he and ZHANG Xu |
| |
Institution: | Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084, China |
| |
Abstract: | Predicting long-term potential human health risks from contaminants in the multimedia environment requires the use of models.However, there is uncertainty associated with these predictions of many parameters which can be represented by ranges or probability distributions rather than single value. Based on a case study with information from an actual site contaminated with benzene, this study describes the application of MMSOILS model to predict health risk and distributions of those predictions generated using Monte Carlo techniques. A sensitivity analysis was performed to evaluate which of the random variables are most important in producing the predicted distributions of health risks. The sensitivity analysis shows that the predicted distributions can be accurately reproduced using a small subset of the random variables. The practical implication of this analysis is the ability to distinguish between important versus unimportant random variables in terms of their sensitivity to selected endpoints. This directly translates into a reduction in data collection and modeling effort. It was demonstrated that how correlation coefficient could be used to evaluate contributions to overall uncertainty from each parameter. The integrated uncertainty analysis shows that although drinking groundwater risk is similar with inhalation air risk, uncertainties of total risk come dominantly from drinking groundwater route. Most percent of the variance of total risk comes from four random variables. |
| |
Keywords: | Monte Carlo sensitivity uncertainty MMSOILS models risk assessment pollutant benzene risk assessment health uncertainties factors percent variance four total come route integrated uncertainty analysis drinking groundwater similar inhalation correlation coefficient used |
本文献已被 CNKI 维普 万方数据 ScienceDirect PubMed 等数据库收录! |
| 点击此处可从《环境科学学报(英文版)》浏览原始摘要信息 |
| 点击此处可从《环境科学学报(英文版)》下载免费的PDF全文 |