Spatial Distribution of Dioxin Plumes in the Vicinity of an Incinerator using Air Dispersion Coupled Geostatistical Model.

Dioxin Contamination;Air Dispersion Coupled With Geostatistical Model;Civil and Environmental Engineering;Engineering;Environmental Engineering

Trinh, Hoa ThiJolliet, Olivier J. ;

University of Michigan

关键词: Dioxin Contamination;    Air Dispersion Coupled With Geostatistical Model;    Civil and Environmental Engineering;    Engineering;    Environmental Engineering;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/64767/htrinh_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

The research develops a regulatory air dispersion coupled geostatistical model to predict congener-specific depositions of polychlorinated dibenzo-p- dioxins (PCDDs) and polychlorinated dibenzo furans (PCDFs)emitted from a historically hazardous waste incinerator. The emission profile of dioxin congeners from the incinerator is hypothesized such that congener attributes impact the depositional pattern, resulting fingerprints in soil, thus better informing exposure models.The work also compares the performances of the two regulatory air dispersion models, ISCST 3 and AERMOD which are precursors to the geostatistical model in predicting dioxins’ air concentrations, dry and wet deposition fluxes and indentifying dioxin removal pathways in gaseous and particulate phase and by dry and wet deposition. Predicted dry and wet deposition fluxes are regressed against the newly collected dioxin soil data in a regression model, generating a spatial trend of dioxin concentrations. The spatial trend of dioxins is incorporated into the geostatistical model using Sequential Gaussian Simulation approach to predict census block-averaged soil concentrations of dioxin Toxic Equivalents (TEQs) to guide the soil sampling campaign. Finally, the coupled uncertainty-based spatial prediction model allows a validation of local uncertainty of the model in predicting spatial distribution of congener specific dioxins in the vicinity of an industrial hazardous waste incinerator.