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1.
Chemosphere ; 47(5): 499-505, 2002 May.
Artigo em Inglês | MEDLINE | ID: mdl-11996125

RESUMO

Per capita boron loads reaching 48 sewage treatment works (STWs) in The Netherlands, Germany, Italy, and the UK have been determined from monitoring data. These have been compared with the per capita input predicted from boron in detergents, as determined from detergent product sales data. The resulting distribution of the ratios of measured boron to boron predicted from consumer usage has a 90th percentile of less than 1.5. Boron has previously been shown to be a good marker for substances contained in detergent products, as it cannot be biodegraded and is not substantially adsorbed in the sewer, and there is little or no removal during sewage treatment processes. The monitoring information on the distribution of boron loads found at the different STWs should thus be indicative of the distribution of other substances released to the environment by detergent products, as specified by the relevant industrial category (IC 5-personal/domestic) in the Technical Guidance Documents. Variation in detergent product consumption figures from 18 European countries is also low, with the country with the highest per capita detergent consumption having only 1.3 times the European average detergent use. Thus the present practice of determining a "reasonable worst case" by multiplying the average per capita consumption by a factor of four to account for geographic differences in distribution, is considered to be inappropriate. This should be replaced by a factor of less than two, which combines within country and between country variations to provide a reasonable worst case approximation of the load reaching the sewage treatment facility.


Assuntos
Boro/análise , Esgotos/química , Poluentes Químicos da Água/análise , Detergentes/análise , Detergentes/economia , Monitoramento Ambiental/métodos , Europa (Continente)
2.
Water Sci Technol ; 43(2): 179-85, 2001.
Artigo em Inglês | MEDLINE | ID: mdl-11380178

RESUMO

The GREAT-ER (Geo-referenced Regional Exposure Assessment Tool for European Rivers) project team has developed and validated an accurate aquatic chemical exposure prediction tool for use within environmental risk assessment schemes. The software system GREAT-ER 1.0 calculates the distribution of predicted environmental concentrations (PECs) of consumer chemicals in surface waters, for individual river stretches as well as for entire catchments. The system uses an ARC/INFO-ArcView (ESRI) based Geographical Information System (GIS) for data storage and visualization, combined with simple mathematical models for prediction of chemical fate. At present, the system contains information for four catchments in Yorkshire, one catchment in Italy, and two in Germany, while other river basins are being added. Great-ER 1.0 has been validated by comparing simulations with the results of an extensive monitoring campaign for two 'down-the-drain' chemicals, i.e. the detergent ingredients boron and Linear Alkylbenzene Sulphonate (LAS). GREAT-ER 1.0 is currently being expanded with models for the terrestrial (diffuse input), air and estaurine compartments.


Assuntos
Monitoramento Ambiental , Modelos Teóricos , Poluição da Água/análise , Geografia , Sistemas de Informação , Medição de Risco , Xenobióticos/análise
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