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Estimating Chemical Footprint on High-resolution Geospatial Grid
We need models to make decisions regarding minimization of chemical impacts on the environment. These models must allow us to make estimations with a minimum amount of data. The USEtox is an example of such a model. However, the Russian Federation (as its districts and some regions) is large in area...
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Published in: | Procedia CIRP 2018, Vol.69, p.469-474 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We need models to make decisions regarding minimization of chemical impacts on the environment. These models must allow us to make estimations with a minimum amount of data. The USEtox is an example of such a model.
However, the Russian Federation (as its districts and some regions) is large in area and contains a wide variety of topography and climatic features. As a result, estimations at the country, district, or region scales, on whole, might lead to incorrect administrative measures. Each administrative unit requires specific assessment and management decisions owing to the peculiarities of the state structure that take into account the above-mentioned features. In addition, there are many point sources causing significant chemical pollution (for example, chemical plants) in territories under consideration. These sources are often located a considerable distance from other sources.
Considering all of the above, we developed an algorithm to calculate the coefficients of chemicals transported between the compartments of the environment on a geospatial grid. The algorithm is based on the UNEP-SETAC scientific consensus USEtox model and a geographic information system (GIS) that provides data of water flows and airflows. We describe the application of the algorithm to the study of Hg2+ transport between Federal Districts of the Russian Federation on a low-resolution grid and to the study of Al3+ transport in the Leningrad Region on a high-resolution 0.5° x 0.5° geospatial grid. |
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ISSN: | 2212-8271 2212-8271 |
DOI: | 10.1016/j.procir.2018.01.001 |