首页    期刊浏览 2024年11月28日 星期四
登录注册

文章基本信息

  • 标题:Relationship between Composition and Toxicity of Motor Vehicle Emission Samples
  • 作者:Jacob D. McDonald ; Ingvar Eide ; JeanClare Seagrave
  • 期刊名称:Environmental Health Perspectives
  • 印刷版ISSN:0091-6765
  • 电子版ISSN:1552-9924
  • 出版年度:2004
  • 卷号:112
  • 期号:15
  • 页码:1527-1538
  • DOI:10.1289/ehp.6976
  • 语种:English
  • 出版社:OCR Subscription Services Inc
  • 摘要:In this study we investigated the statistical relationship between particle and semivolatile organic chemical constituents in gasoline and diesel vehicle exhaust samples, and toxicity as measured by inflammation and tissue damage in rat lungs and mutagenicity in bacteria. Exhaust samples were collected from “normal” and “high-emitting” gasoline and diesel light-duty vehicles. We employed a combination of principal component analysis (PCA) and partial least-squares regression (PLS; also known as projection to latent structures) to evaluate the relationships between chemical composition of vehicle exhaust and toxicity. The PLS analysis revealed the chemical constituents covarying most strongly with toxicity and produced models predicting the relative toxicity of the samples with good accuracy. The specific nitro-polycyclic aromatic hydrocarbons important for mutagenicity were the same chemicals that have been implicated by decades of bioassay-directed fractionation. These chemicals were not related to lung toxicity, which was associated with organic carbon and select organic compounds that are present in lubricating oil. The results demonstrate the utility of the PCA/PLS approach for evaluating composition–response relationships in complex mixture exposures and also provide a starting point for confirming causality and determining the mechanisms of the lung effects.
  • 关键词:diesel exhaust; gasoline exhaust; hopane; mutagenicity; PAHs; particulate matter health effects; principal component analysis; semivolatile organic carbon; sterane; toxicity of motor vehicle emissions
Loading...
联系我们|关于我们|网站声明
国家哲学社会科学文献中心版权所有