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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| creator | Knodel, J. Geißen, S.-U. Broll, J. Dünnbier, U. |
| description | 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. |
| doi_str_mv | 10.1016/j.jenvman.2011.07.004 |
| format | Article |
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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.</description><identifier>ISSN: 0301-4797</identifier><identifier>EISSN: 1095-8630</identifier><identifier>DOI: 10.1016/j.jenvman.2011.07.004</identifier><identifier>PMID: 21821343</identifier><identifier>CODEN: JEVMAW</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Animal, plant and microbial ecology ; Applied ecology ; Berlin ; Biological and medical sciences ; Computer Simulation ; Conservation, protection and management of environment and wildlife ; Contrast media ; Contrast Media - isolation & purification ; Data analysis ; Decision Support Techniques ; Dispersion of trace pollutants ; Ecotoxicology, biological effects of pollution ; Environmental management ; Fundamental and applied biological sciences. Psychology ; General aspects ; Hospitals ; Hydrologic cycle ; Identification ; Inhabitants ; Mathematical models ; Medical treatment ; Models, Theoretical ; Point sources ; Radioactive waste ; Simulation ; Source identification ; Uncertainty ; Urban areas ; Waste management ; Water Cycle ; Water Pollutants, Chemical - isolation & purification ; Water pollution ; Water resources ; Water Supply ; X-ray contrast media ; X-rays</subject><ispartof>Journal of environmental management, 2011-11, Vol.92 (11), p.2913-2923</ispartof><rights>2011 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2011 Elsevier Ltd. All rights reserved.</rights><rights>Copyright Academic Press Ltd. Nov 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c518t-6e36efb89bdd687111ef6057c7dba5f1b941fadd183b0a05ec270555b9b5256e3</citedby><cites>FETCH-LOGICAL-c518t-6e36efb89bdd687111ef6057c7dba5f1b941fadd183b0a05ec270555b9b5256e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jenvman.2011.07.004$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24537278$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21821343$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Knodel, J.</creatorcontrib><creatorcontrib>Geißen, S.-U.</creatorcontrib><creatorcontrib>Broll, J.</creatorcontrib><creatorcontrib>Dünnbier, U.</creatorcontrib><title>Simulation and source identification of X-ray contrast media in the water cycle of Berlin</title><title>Journal of environmental management</title><addtitle>J Environ Manage</addtitle><description>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.</description><subject>Animal, plant and microbial ecology</subject><subject>Applied ecology</subject><subject>Berlin</subject><subject>Biological and medical sciences</subject><subject>Computer Simulation</subject><subject>Conservation, protection and management of environment and wildlife</subject><subject>Contrast media</subject><subject>Contrast Media - isolation & purification</subject><subject>Data analysis</subject><subject>Decision Support Techniques</subject><subject>Dispersion of trace pollutants</subject><subject>Ecotoxicology, biological effects of pollution</subject><subject>Environmental management</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Hospitals</subject><subject>Hydrologic cycle</subject><subject>Identification</subject><subject>Inhabitants</subject><subject>Mathematical models</subject><subject>Medical treatment</subject><subject>Models, Theoretical</subject><subject>Point sources</subject><subject>Radioactive waste</subject><subject>Simulation</subject><subject>Source identification</subject><subject>Uncertainty</subject><subject>Urban areas</subject><subject>Waste management</subject><subject>Water Cycle</subject><subject>Water Pollutants, Chemical - isolation & purification</subject><subject>Water pollution</subject><subject>Water resources</subject><subject>Water Supply</subject><subject>X-ray contrast media</subject><subject>X-rays</subject><issn>0301-4797</issn><issn>1095-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqN0c-L1TAQwPEiivtc_ROUIoheWmeappOeRBd_wYIHFfQU0nSKKW26Ju3K--_N4z0VPOieeshnhjTfLHuIUCJg83wsR_bXs_FlBYglUAlQ38p2CK0sVCPgdrYDAVjU1NJZdi_GEQBEhXQ3O6tQVShqscu-fnTzNpnVLT43vs_jsgXLuevZr25w9niyDPmXIph9bhe_BhPXfObemdz5fP3G-Q-zcsjt3k58oK84TM7fz-4MZor84PQ9zz6_ef3p4l1x-eHt-4uXl4WVqNaiYdHw0Km26_tGESLy0IAkS31n5IBdW-Ng-h6V6MCAZFsRSCm7tpOVTNPn2dPj3quwfN84rnp20fI0Gc_LFrVqW5TU1OoGslGiBnEDqVqkmgiSfPZPiUSEUpKkRB__Rcf02D69TdpHrSIJMiF5RDYsMQYe9FVwswl7jaAP4fWoT-H1IbwG0il8mnt0Wr51qc3vqV-lE3hyAiZaMw3BeOviH1dLQRUdfv3F0XFqdu046Ggde5t6B7ar7hf3n6v8BN_qzMc</recordid><startdate>20111101</startdate><enddate>20111101</enddate><creator>Knodel, J.</creator><creator>Geißen, S.-U.</creator><creator>Broll, J.</creator><creator>Dünnbier, U.</creator><general>Elsevier Ltd</general><general>Elsevier</general><general>Academic Press Ltd</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7SN</scope><scope>7ST</scope><scope>7UA</scope><scope>8BJ</scope><scope>C1K</scope><scope>F1W</scope><scope>FQK</scope><scope>H97</scope><scope>JBE</scope><scope>L.G</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>7X8</scope><scope>7U6</scope></search><sort><creationdate>20111101</creationdate><title>Simulation and source identification of X-ray contrast media in the water cycle of Berlin</title><author>Knodel, J. ; Geißen, S.-U. ; Broll, J. ; Dünnbier, U.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c518t-6e36efb89bdd687111ef6057c7dba5f1b941fadd183b0a05ec270555b9b5256e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Animal, plant and microbial ecology</topic><topic>Applied ecology</topic><topic>Berlin</topic><topic>Biological and medical sciences</topic><topic>Computer Simulation</topic><topic>Conservation, protection and management of environment and wildlife</topic><topic>Contrast media</topic><topic>Contrast Media - isolation & purification</topic><topic>Data analysis</topic><topic>Decision Support Techniques</topic><topic>Dispersion of trace pollutants</topic><topic>Ecotoxicology, biological effects of pollution</topic><topic>Environmental management</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>Hospitals</topic><topic>Hydrologic cycle</topic><topic>Identification</topic><topic>Inhabitants</topic><topic>Mathematical models</topic><topic>Medical treatment</topic><topic>Models, Theoretical</topic><topic>Point sources</topic><topic>Radioactive waste</topic><topic>Simulation</topic><topic>Source identification</topic><topic>Uncertainty</topic><topic>Urban areas</topic><topic>Waste management</topic><topic>Water Cycle</topic><topic>Water Pollutants, Chemical - isolation & purification</topic><topic>Water pollution</topic><topic>Water resources</topic><topic>Water Supply</topic><topic>X-ray contrast media</topic><topic>X-rays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Knodel, J.</creatorcontrib><creatorcontrib>Geißen, S.-U.</creatorcontrib><creatorcontrib>Broll, J.</creatorcontrib><creatorcontrib>Dünnbier, U.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>International Bibliography of the Social Sciences</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>International Bibliography of the Social Sciences</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Sustainability Science Abstracts</collection><jtitle>Journal of environmental management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Knodel, J.</au><au>Geißen, S.-U.</au><au>Broll, J.</au><au>Dünnbier, U.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulation and source identification of X-ray contrast media in the water cycle of Berlin</atitle><jtitle>Journal of environmental management</jtitle><addtitle>J Environ Manage</addtitle><date>2011-11-01</date><risdate>2011</risdate><volume>92</volume><issue>11</issue><spage>2913</spage><epage>2923</epage><pages>2913-2923</pages><issn>0301-4797</issn><eissn>1095-8630</eissn><coden>JEVMAW</coden><abstract>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.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>21821343</pmid><doi>10.1016/j.jenvman.2011.07.004</doi><tpages>11</tpages></addata></record> |
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| subjects | Animal, plant and microbial ecology Applied ecology Berlin Biological and medical sciences Computer Simulation Conservation, protection and management of environment and wildlife Contrast media Contrast Media - isolation & purification Data analysis Decision Support Techniques Dispersion of trace pollutants Ecotoxicology, biological effects of pollution Environmental management Fundamental and applied biological sciences. Psychology General aspects Hospitals Hydrologic cycle Identification Inhabitants Mathematical models Medical treatment Models, Theoretical Point sources Radioactive waste Simulation Source identification Uncertainty Urban areas Waste management Water Cycle Water Pollutants, Chemical - isolation & purification Water pollution Water resources Water Supply X-ray contrast media X-rays |
| title | Simulation and source identification of X-ray contrast media in the water cycle of Berlin |
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