An integrated fuzzy-stochastic modeling approach for assessing health-impact risk from air pollution
An integrated fuzzy-stochastic modeling approach for assessing health-impact risk from air pollution
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DOI：
10.1007/s00477-007-0187-1
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发表时间：
2008-10-01
影响因子：
4.2
通讯作者：
Zou, Yun
中科院分区：
文献类型：
--
作者：
Li, Heng L.;Huang, Guo H.;Zou, Yun
周围环境中高浓度的空气污染物会导致人类社区的呼吸问题。有效评估空气污染对健康的影响风险，对于支持相关检测、预防和纠正工作的决策非常重要。然而，可用于环境/健康风险评估的信息质量往往不够令人满意，不能以确定性数字表示。随机方法是处理这些不确定性的方法之一，它可以将不确定信息表示为概率分布。然而，如果不能将不确定性表示为概率，则可以通过模糊隶属度函数来处理它们。在这项研究中，开发了一种综合模糊-随机建模(IFSM)方法来评估空气污染对哮喘易感性的影响。这一发展是基于对环境中SO(2)去向的蒙特卡罗模拟、基于模拟结果的SO(2)浓度检测、使用模糊隶属函数量化评价标准以及基于模糊和随机信息的组合的风险评估。综合风险管理包括：(A)模拟污染物在环境中的去向，考虑源/介质的不确定性；(B)在不确定的人类暴露途径、暴露动态和SPG反应变化下制定模糊的空气质量管理标准；以及(C)在污染物水平和健康影响(即哮喘易感性)的组合模糊/随机输入的复杂情况下进行综合风险评估。将该模型应用于区域空气质量管理的研究。得出了合理的结果，这对评估空气污染的健康风险是有用的。它们还为区域环境管理和城市规划提供支持。
High concentrations of air pollutants in the ambient environment can result in breathing problems with human communities. Effective assessment of health-impact risk from air pollution is important for supporting decisions of the related detection, prevention, and correction efforts. However, the quality of information available for environmental/health risk assessment is often not satisfactory enough to be presented as deterministic numbers. Stochastic method is one of the methods for tackling those uncertainties, by which uncertain information can be presented as probability distributions. However, if the uncertainties can not be presented as probabilities, they can then be handled through fuzzy membership functions. In this study, an integrated fuzzy-stochastic modeling (IFSM) approach is developed for assessing air pollution impacts towards asthma susceptibility. This development is based on Monte Carlo simulation for the fate of SO(2) in the ambient environment, examination of SO(2) concentrations based on the simulation results, quantification of evaluation criteria using fuzzy membership functions, and risk assessment based on the combined fuzzy-stochastic information. The IFSM entails (a) simulation for the fate of pollutants in ambient environment, with the consideration of source/medium uncertainties, (b) formulation of fuzzy air quality management criteria under uncertain human-exposure pathways, exposure dynamics, and SPG-response variations, and (c) integrated risk assessment under complexities of the combined fuzzy/stochastic inputs of contamination level and health effect (i.e., asthma susceptibility). The developed IFSM is applied to a study of regional air quality management. Reasonable results have been generated, which are useful for evaluating health risks from air pollution. They also provide support for regional environmental management and urban planning.