Data requirements of GREAT-ER: Modelling and validation using LAS in four UK catchments
Higher-tier environmental risk assessments on “down-the-drain” chemicals in river networks can be conducted using models such as GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers). It is important these models are evaluated and their sensitivities to input variable...
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| Veröffentlicht in: | Environmental pollution (1987) 2009-10, Vol.157 (10), p.2610-2616 |
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| creator | Price, Oliver R. Munday, Dawn K. Whelan, Mick J. Holt, Martin S. Fox, Katharine K. Morris, Gerard Young, Andrew R. |
| description | Higher-tier environmental risk assessments on “down-the-drain” chemicals in river networks can be conducted using models such as GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers). It is important these models are evaluated and their sensitivities to input variables understood. This study had two primary objectives: evaluate GREAT-ER model performance, comparing simulated modelled predictions for LAS (linear alkylbenzene sulphonate) with measured concentrations, for four rivers in the UK, and investigate model sensitivity to input variables. We demonstrate that the GREAT-ER model is very sensitive to variability in river discharges. However it is insensitive to the form of distributions used to describe chemical usage and removal rate in sewage treatment plants (STPs). It is concluded that more effort should be directed towards improving empirical estimates of effluent load and reducing uncertainty associated with usage and removal rates in STPs. Simulations could be improved by incorporating the effect of river depth on dissipation rates.
Validation of GREAT-ER. |
| doi_str_mv | 10.1016/j.envpol.2009.05.010 |
| format | Article |
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Validation of GREAT-ER.</description><subject>Alkanesulfonic Acids - analysis</subject><subject>Alkylbenzene</subject><subject>Animal, plant and microbial ecology</subject><subject>Applied ecology</subject><subject>Applied sciences</subject><subject>Assessments</subject><subject>Biological and medical sciences</subject><subject>Computer simulation</subject><subject>Continental surface waters</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Ecotoxicology, biological effects of pollution</subject><subject>Engineering and environment geology. Geothermics</subject><subject>Environmental exposure assessment</subject><subject>environmental monitoring</subject><subject>Environmental Monitoring - instrumentation</subject><subject>Environmental Monitoring - methods</subject><subject>Exact sciences and technology</subject><subject>Fresh water environment</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>geographic information systems</subject><subject>GREAT-ER</subject><subject>LAS</subject><subject>Mathematical models</subject><subject>model validation</subject><subject>Models, Theoretical</subject><subject>Natural water pollution</subject><subject>Networks</subject><subject>personal care products</subject><subject>pollutants</subject><subject>Pollution</subject><subject>Pollution, environment geology</subject><subject>prediction</subject><subject>risk assessment</subject><subject>Rivers</subject><subject>Rivers - chemistry</subject><subject>simulation models</subject><subject>spatial distribution</subject><subject>stream flow</subject><subject>temporal variation</subject><subject>United Kingdom</subject><subject>Validation</subject><subject>Water Pollutants, Chemical - analysis</subject><subject>Water Pollution</subject><subject>Water treatment and pollution</subject><issn>0269-7491</issn><issn>1873-6424</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqF0stuEzEUBuARAtG08AYIvOGymXB8n2GBFLWhIIKQ2kYsLcc-UxxNZlJ7JhJvj0Mi2IWVJes7F-t3UbygMKVA1fv1FLvdtm-nDKCegpwChUfFhFaal0ow8biYAFN1qUVNz4rzlNYAIDjnT4szWksmuIBJ8ePKDpZEfBhDxA12QyJ9Q65v5rO7cn7zgXzrPbZt6O6J7TzZ2TZ4O4S-I2PaXy5mtyR0pOnHSJZfibOD-_mny7PiSWPbhM-P50Wx_DS_u_xcLr5ff7mcLUonKQylWGHjnPWyUiteKc9rzTVVvuLIVlqgQC6sUxaYkyC9t5JTpJTWjnklEPlF8fbQdxv7hxHTYDYhubyy7bAfk9GcS61AVlm-OSm50LyqavpfyECrLFmG705CqrWmAFypTMWButinFLEx2xg2Nv4yFMw-TrM2hzjNPk4D0uQ4c9nL44RxtUH_r-iYXwavj8AmZ9sm2s6F9NcxWsn8pv2qrw6usb2x9zGb5S0DyvNoTYXSWXw8CMxp7QJGk1zAzqHPH8MNxvfh9K6_AQkgxoU</recordid><startdate>20091001</startdate><enddate>20091001</enddate><creator>Price, Oliver R.</creator><creator>Munday, Dawn K.</creator><creator>Whelan, Mick J.</creator><creator>Holt, Martin S.</creator><creator>Fox, Katharine K.</creator><creator>Morris, Gerard</creator><creator>Young, Andrew R.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>FBQ</scope><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>7SU</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope><scope>7X8</scope></search><sort><creationdate>20091001</creationdate><title>Data requirements of GREAT-ER: Modelling and validation using LAS in four UK catchments</title><author>Price, Oliver R. ; Munday, Dawn K. ; Whelan, Mick J. ; Holt, Martin S. ; Fox, Katharine K. ; Morris, Gerard ; Young, Andrew R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c510t-4befccad586b386d3973716d83e2b74e4e34ac6a02c505dda531e1119c2d64ee3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Alkanesulfonic Acids - analysis</topic><topic>Alkylbenzene</topic><topic>Animal, plant and microbial ecology</topic><topic>Applied ecology</topic><topic>Applied sciences</topic><topic>Assessments</topic><topic>Biological and medical sciences</topic><topic>Computer simulation</topic><topic>Continental surface waters</topic><topic>Earth sciences</topic><topic>Earth, ocean, space</topic><topic>Ecotoxicology, biological effects of pollution</topic><topic>Engineering and environment geology. Geothermics</topic><topic>Environmental exposure assessment</topic><topic>environmental monitoring</topic><topic>Environmental Monitoring - instrumentation</topic><topic>Environmental Monitoring - methods</topic><topic>Exact sciences and technology</topic><topic>Fresh water environment</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>geographic information systems</topic><topic>GREAT-ER</topic><topic>LAS</topic><topic>Mathematical models</topic><topic>model validation</topic><topic>Models, Theoretical</topic><topic>Natural water pollution</topic><topic>Networks</topic><topic>personal care products</topic><topic>pollutants</topic><topic>Pollution</topic><topic>Pollution, environment geology</topic><topic>prediction</topic><topic>risk assessment</topic><topic>Rivers</topic><topic>Rivers - chemistry</topic><topic>simulation models</topic><topic>spatial distribution</topic><topic>stream flow</topic><topic>temporal variation</topic><topic>United Kingdom</topic><topic>Validation</topic><topic>Water Pollutants, Chemical - analysis</topic><topic>Water Pollution</topic><topic>Water treatment and pollution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Price, Oliver R.</creatorcontrib><creatorcontrib>Munday, Dawn K.</creatorcontrib><creatorcontrib>Whelan, Mick J.</creatorcontrib><creatorcontrib>Holt, Martin S.</creatorcontrib><creatorcontrib>Fox, Katharine K.</creatorcontrib><creatorcontrib>Morris, Gerard</creatorcontrib><creatorcontrib>Young, Andrew R.</creatorcontrib><collection>AGRIS</collection><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>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Environmental pollution (1987)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Price, Oliver R.</au><au>Munday, Dawn K.</au><au>Whelan, Mick J.</au><au>Holt, Martin S.</au><au>Fox, Katharine K.</au><au>Morris, Gerard</au><au>Young, Andrew R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data requirements of GREAT-ER: Modelling and validation using LAS in four UK catchments</atitle><jtitle>Environmental pollution (1987)</jtitle><addtitle>Environ Pollut</addtitle><date>2009-10-01</date><risdate>2009</risdate><volume>157</volume><issue>10</issue><spage>2610</spage><epage>2616</epage><pages>2610-2616</pages><issn>0269-7491</issn><eissn>1873-6424</eissn><coden>ENVPAF</coden><abstract>Higher-tier environmental risk assessments on “down-the-drain” chemicals in river networks can be conducted using models such as GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers). It is important these models are evaluated and their sensitivities to input variables understood. This study had two primary objectives: evaluate GREAT-ER model performance, comparing simulated modelled predictions for LAS (linear alkylbenzene sulphonate) with measured concentrations, for four rivers in the UK, and investigate model sensitivity to input variables. We demonstrate that the GREAT-ER model is very sensitive to variability in river discharges. However it is insensitive to the form of distributions used to describe chemical usage and removal rate in sewage treatment plants (STPs). It is concluded that more effort should be directed towards improving empirical estimates of effluent load and reducing uncertainty associated with usage and removal rates in STPs. Simulations could be improved by incorporating the effect of river depth on dissipation rates.
Validation of GREAT-ER.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>19524340</pmid><doi>10.1016/j.envpol.2009.05.010</doi><tpages>7</tpages></addata></record> |
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| issn | 0269-7491 1873-6424 |
| language | eng |
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| subjects | Alkanesulfonic Acids - analysis Alkylbenzene Animal, plant and microbial ecology Applied ecology Applied sciences Assessments Biological and medical sciences Computer simulation Continental surface waters Earth sciences Earth, ocean, space Ecotoxicology, biological effects of pollution Engineering and environment geology. Geothermics Environmental exposure assessment environmental monitoring Environmental Monitoring - instrumentation Environmental Monitoring - methods Exact sciences and technology Fresh water environment Fundamental and applied biological sciences. Psychology geographic information systems GREAT-ER LAS Mathematical models model validation Models, Theoretical Natural water pollution Networks personal care products pollutants Pollution Pollution, environment geology prediction risk assessment Rivers Rivers - chemistry simulation models spatial distribution stream flow temporal variation United Kingdom Validation Water Pollutants, Chemical - analysis Water Pollution Water treatment and pollution |
| title | Data requirements of GREAT-ER: Modelling and validation using LAS in four UK catchments |
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