首页 | 本学科首页   官方微博 | 高级检索  
     


Implications of a statistical occurrence model for mixture toxicity estimation
Authors:Nur H. Orak  Mitchell J. Small
Affiliation:1. Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA;2. Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA
Abstract:This study provides a method for characterizing the effects of concentration variability and correlation among co-acting compounds on mixture toxicity, considering the implications of missing chemical data. The method is explored by developing a set of multiple occurrence scenarios for mixtures of related chemicals. The calculations are performed for hypothetical mixtures of a group of ten synthetic antibiotics that have been tested on marine bacterium to fit dose-response relationships for long-term bioluminescence inhibition of Vibrio fischeri. Mixture toxicities are computed and compared for the assumptions of independent joint action theory and concentration/dose addition theory. The study results show that higher variability in concentrations is associated with higher effective (average) mixture toxicity, in this application by as much as a factor of ten for mixtures with highly variable component concentrations. Moreover, omitting the most toxic compounds caused mixture toxicities to be underestimated by a factor of approximately two. We recommend a pre-assessment of the effect of different chemical occurrence patterns and variability on mixture toxicity to help prioritize needs for further co-occurrence data and toxicity studies.
Keywords:mixture toxicology  risk assessment  statistical model  chemical mixtures  chemical occurrence  computational modeling
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号