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GIS Based Chemical Fate Modeling: Principles and Applications by Alberto Pistocchi

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Chapter 11

Soft Computing Methods for the Overlaying of Chemical Data with Other Spatially Varying Parameters

Alberto Pistocchi, Davide Geneletti, Ezio Crestaz and Paolo Mazzoli

11.1 Introduction

In previous chapters, we have discussed methods for the modeling of chemicals. Usually, models are developed for the purpose of analyzing where an observed contamination comes from (inverse modeling), or where a contaminant from a given emission source goes (direct modeling). Direct modeling is the typical mode when in need of simulating scenarios, the so called what-if approach. A special case of what-if simulation mode is when one does not know a priori where an emission may happen, and aims at exploring systematically the different effects of such an emission at different spatial locations, by applying a model to each location. The model results are again concentrations or fluxes of chemicals that correspond to a hypothetical emission. For simplicity, thanks to the linearity of the ADE, a unit emission rate may be considered, as concentrations are always proportional to it and may consequently be computed a posteriori for a generic value of the emission rate of a chemical. The comparative assessment of effects of an emission at different locations yields results that can be summarized through appropriate indicators, providing support to decision makers about certain options. For instance, one may want to identify the variation in population exposure to a certain chemical emitted from ...

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