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首页> 外文期刊>Journal of Hazardous Materials >Quantitative risk assessment of stack emissions from municipal waste combustors
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Quantitative risk assessment of stack emissions from municipal waste combustors

机译:市政垃圾燃烧器烟囱排放的定量风险评估

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摘要

Multi-pathway risk assessment (MRA) is a tool for evaluating the possibility of adverse effects to human health that may result from contaminant releases from municipal solid waste combustors (MWCs) and other sources of air pollution. An MRA attempts to model the movement of pollutants within the environment to various points at which they may be contacted by people, beginning with inhalation of contaminated air and continuing with indirect pathways such as food chain exposures that entail contaminant transfer and accumulation through several media. MRAs of MWCs date back to the mid-1980s, and are rooted in methods developed to assess the consequences of radionuclide releases from nuclear power generation. A detailed example of a typical MRA is presented that follows the classic four-stage risk assessment paradigm (Valberg et al., 1995). MRA methods, however, continue to be enhanced and refined by recent research. A number of current risk assessment topics are explored that are new to traditional MRAs and may serve to re-focus our collective efforts. The purpose of and demands on MRAs must be considered. A philosophical shift toward placing greater realism in MRAs underscores the importance of uncertainties inherent to risk estimates. Tools such as probabilistic risk assessment techniques must be developed and endorsed so that decision-makers may intelligently utilize the information provided by MRAs.
机译:多路径风险评估(MRA)是一种工具,用于评估城市固体废物燃烧器(MWC)和其他空气污染源释放的污染物可能对人体健康造成不利影响的可能性。 MRA试图模拟污染物在环境中向人们可能接触到的各个点的移动,从吸入污染空气开始,再到间接途径(例如食物链暴露),这种途径需要污染物通过多种介质转移和积累。 MWC的MRA可以追溯到1980年代中期,其根源在于评估核发电中放射性核素释放后果的开发方法。提出了典型MRA的详细示例,该示例遵循经典的四阶段风险评估范例(Valberg等,1995)。然而,最近的研究继续增加和完善了MRA方法。探索了许多当前的风险评估主题,这些主题对于传统MRA来说是新的,可能有助于重新集中我们的集体努力。必须考虑MRA的目的和要求。朝着将更大的现实性置于MRA中的理念上的转变强调了风险估计所固有的不确定性的重要性。必须开发并认可诸如概率风险评估技术之类的工具,以便决策者可以智能地利用MRA提供的信息。

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