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- W3186819869 abstract "The fast and accurate identification of air pollutant release effectively improved the emergency management for fine chemical industrial parks. The pollutant emission parameters could be estimated with the observed pollutant and meteorology data using an air dispersion model. Most of the fast response source term estimation methods are based on the Gaussian plume model for the low computation complexity. The concentration profile estimated by the Gaussian plume model can hardly represent the observation result affected by the complicated terrain with buildings in dense industrial area. Besides, the dispersion models with well characterized building profile like computation fluid dynamic (CFD) are time consuming. In this paper, a metamodelling method with downwash effect of buildings in the domain to estimate the air pollutant emission is proposed. The dispersion model (Aermod) with combined plume rise and building down wash (PRIME) model preferred by U.S. Environmental Protection Agency is used to establish an emission inventory which covers most possible release scenarios in a dedicated area such as a chemical industrial park. The initial emission inventory is then fed to a neural network. The emission inventory will be updated as well as the neural network with an increasing number of scenarios until the trained neural network meets the pre-set criteria. The well-trained neural network is then used to predict the source emissions with observed data collected in a fine chemical industrial park. A case study is performed with a localized Aermod model with geometry and surface character data collected from an industrial park. The results show that the building down wash effect in the industrial parks is responsible for some source estimating error produced by the inverse Gaussian dispersion model. It shows the advance of time consumption and competitive prediction accuracy compared to typical least square in version methods." @default.
- W3186819869 created "2021-08-02" @default.
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- W3186819869 date "2021-01-01" @default.
- W3186819869 modified "2023-10-18" @default.
- W3186819869 title "A Metamodelling Approach for Air Pollution Source Estimation" @default.
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- W3186819869 doi "https://doi.org/10.1016/b978-0-323-88506-5.50122-4" @default.
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