Simulation and source identification of X-ray contrast media in the water cycle of Berlin
This article describes the development of a model to simulate the fate of iodinated X-ray contrast media (XRC) in the water cycle of the German capital, Berlin. It also handles data uncertainties concerning the different amounts and sources of input for XRC via source densities in single districts f...
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Veröffentlicht in: | Journal of environmental management 2011-11, Vol.92 (11), p.2913-2923 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This article describes the development of a model to simulate the fate of iodinated X-ray contrast media (XRC) in the water cycle of the German capital, Berlin. It also handles data uncertainties concerning the different amounts and sources of input for XRC via source densities in single districts for the XRC usage by inhabitants, hospitals, and radiologists. As well, different degradation rates for the behavior of the adsorbable organic iodine (AOI) were investigated in single water compartments.
The introduced model consists of mass balances and includes, in addition to naturally branched bodies of water, the water distribution network between waterways and wastewater treatment plants, which are coupled to natural surface waters at numerous points. Scenarios were calculated according to the data uncertainties that were statistically evaluated to identify the scenario with the highest agreement among the provided measurement data.
The simulation of X-ray contrast media in the water cycle of Berlin showed that medical institutions have to be considered as point sources for congested urban areas due to their high levels of X-ray contrast media emission. The calculations identified hospitals, represented by their capacity (number of hospital beds), as the most relevant point sources, while the inhabitants served as important diffusive sources. Deployed for almost inert substances like contrast media, the model can be used for qualitative statements and, therefore, as a decision-support tool.
► Modeling the dispersion of X-ray contrast media in the water cycle of Berlin. ► Coupling of water distribution networks and surface waters. ► Handling of data uncertainties. ► Calculation of developed scenarios. ► Identification of hospitals and inhabitants as most relevant sources. |
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ISSN: | 0301-4797 1095-8630 |
DOI: | 10.1016/j.jenvman.2011.07.004 |