Miller F J, Graham J A, Gardner D E
Environ Health Perspect. 1983 Oct;52:169-76. doi: 10.1289/ehp.8352169.
The Clean Air Act is the basic U.S. Federal law for controlling air pollution. Under Sections 108 and 109, primary (health) national ambient air quality standards (NAAQS) can be set for pollutants which are ubiquitous in the ambient air. The standard-setting process includes a comprehensive summary of scientific information on effects and controls in criteria and control techniques, and the selection of an appropriate standard which, in the judgment of the Administrator, protects the health of normal and susceptible subpopulations with an adequate margin of safety. Determining the adequacy of existing NAAQS or establishing new standards requires that the scientific information base be evaluated to assess pollutant effects on public health. Improvements in this process can be accomplished not only through new health effects research, but also through improved use of currently available data. The commonality joining these two efforts is in the area of extrapolation modeling, which is the topic of this paper. Extrapolation modeling involves determining the effective dose delivered to the target organ of several species and the sensitivity of the target organ to that dose so that effective pollutant concentrations can be estimated across species. This in turn allows greater utilization of the results from animals in making judgments about the effects in man from exposure to a given pollutant.
《清洁空气法》是美国控制空气污染的基本联邦法律。根据第108条和第109条,可以针对环境空气中普遍存在的污染物制定主要(健康)国家环境空气质量标准(NAAQS)。标准制定过程包括对关于污染物影响及标准和控制技术中控制措施的科学信息进行全面总结,以及选择适当的标准,在管理员看来,该标准能以足够的安全余量保护正常和易感亚人群的健康。确定现有国家环境空气质量标准是否充分或制定新的标准需要对科学信息库进行评估,以评估污染物对公众健康的影响。这一过程的改进不仅可以通过新的健康影响研究来实现,还可以通过更好地利用现有数据来实现。将这两项工作联系起来的共同之处在于外推建模领域,这也是本文的主题。外推建模涉及确定几种物种输送到靶器官的有效剂量以及靶器官对该剂量的敏感性,以便能够跨物种估计有效污染物浓度。这反过来又能在判断人类接触特定污染物的影响时,更充分地利用来自动物实验的结果。