An integrated fuzzy-stochastic modeling approach for assessing health-impact risk from air pollution |
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Authors: | Heng L Li Guo H Huang Yun Zou |
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Institution: | (1) Environmental Systems Engineering Program, University of Regina, Regina, SK, S4S 0A2, Canada;(2) Chinese Research Academy of Environmental Science, North China Electric Power University, Beijing, 100012-102206, China;(3) Center for studies in Energy and Environment, University of Regina, Regina, SK, S4S 0A2, Canada |
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Abstract: | 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 SO2 in the ambient environment, examination of SO2 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. |
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Keywords: | Air pollution Decision support Fuzzy Planning Risk assessment Simulation Stochastic Uncertainty |
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