Microenvironmental modeling integrated with Geographic Information Systems for exposure analysis

Exposure analysis is an integral component of environmental risk assessment, which provides estimates of potential exposure (or contact concentration), and internal dose of a biological receptor, or living organism to a contaminant. Microenvironmental models estimate the potential exposure to a contaminant by mathematically describing the physical and chemical processes that lead to an individual's contact with the contaminant.; Potential exposure of an individual to a contaminant is traditionally estimated based on the following: from estimates of ambient concentrations of macroenvironmental or large urban scale models, and from field sampling of the contaminant concentration an individual can come in contact with. Mechanistic microenvironmental models form a missing link between these two approaches, as they can incorporate ambient/outdoor concentration estimates and microenvironmental/indoor measured concentrations.; The first objective of this study is the development and evaluation of microenvironmental models, that can mechanistically account for multimedia interactions to estimate potential exposure. A microenvironmental model was developed which can account for arbitrarily defined gas phase chemistry mechanisms indoors and outdoors, and which couples the fate and transport of contaminants through the different media. This is a refinement over typical microenvironmental models that are multizonal mass balance models with linear decay type chemical transformations.; Exposure assessment studies require datasets from diverse studies. These datasets include emission levels, meteorological data and subsurface conditions (presence and characteristics of aquifers, soil and sediment flow, transport and fate characteristics, etc.), population dynamics information, and environmental impact studies. These datasets are each collected with specific temporal and spatial scales, i.e. they are spatio-temporal in nature. The spatial nature of environmental data warrants the use of tools like Geographic Information Systems (GIS) for spatial analyses.; The second objective of this study is the development and demonstration of a research prototype (GridLib), that integrates exposure models in a "nested-grid" structure, to facilitate the flow of information from large scale to small scale environmental models used in exposure assessment. This is achieved by coupling with data management tools such as GIS. The advantage of saving all forms of data in GIS format is that it makes attribute specific spatial queries more accessible to an exposure analyst.