As one of the leading global research companies, P&G often enters into research partnerships. P&G itself began as a partnership, and this continues to be a key component in the company’s growth.  In 2001, the open innovation concept of ‘Connect and Develop’ , focusing on forming partnerships to increase innovation was developed. P&G continues to foster research partnerships, whether it involves supporting the work of PhD candidates, working with other companies, universities or industry associations.

A good example of an industry research partnership in the environmental field is when P&G worked with CEFIC, the European Chemical Industry Council, under the Long-Range Research Initiative (CEFIC-LRI, ) programme, to develop GREAT-ER, a GIS-assisted computer model for tiered risk assessment.


    Use of GREAT-ER as an advanced exposure model in a tiered risk assessment system. GREAT-ER provides a site specific refinement over the standard regulatory model EUSES. Fig. 1: Use of GREAT-ER as an advanced exposure model in a tiered risk assessment system. GREAT-ER provides a site specific refinement over the standard regulatory model EUSES.

    Example exposure simulation in the Rur river, Germany, with GREAT-ER Desktop 3.0 Fig. 2: Example exposure simulation in the Rur river, Germany, with GREAT-ER Desktop 3.0

    GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers) is a GIS-assisted computer model for risk assessment and management of chemicals in river basins. It can, for example, be used in the context of European chemicals risk assessment process (REACH), and in the EU Water Framework Directive (WFD).  The model is implemented as part of a software system that combines a GIS (Geographic Information System) with fate models to produce a simple and clear visualization of predicted chemical concentrations and water quality along a river (Fig. 2).  Conceptually similar exposure models exist for the USA, e.g. iSTREEM. 

    Since the release by ECETOC of the original model in 1999 (GREAT-ER 1.0) a number of regional projects have been initiated by various organizations with the aim of exploring and expanding the different applications of the model. To facilitate this process, the model system was re-implemented with a modular architecture and a database back-end in 2003 (GREAT-ER Desktop and GREAT-ER Web). Over the years, the GREAT-ER model has served a worldwide user community, and currently more than 170 different scientific papers refer to the development or application of the model. P&G uses GREAT-ER for the more complex and/or detailed risk assessments, sometimes in combination with field monitoring work. 

    Under the sponsorship of the CEFIC-LRI programme the package has now been updated again as GREAT-ER 3.0 (2011).  Most notably, the database has been replaced by the Open Source Software PostgreSQL. For the first time, the entire system can be installed without any software licence fee, and the scientific community is welcome to analyze and enhance the Free Software GREAT-ER.  On the model side, GREAT-ER 3.0 now also includes a sediment extension, and the possibility to model lakes as part of a river basin.

    Information on GREAT-ER and updates on different projects initiatives can be found at
    Download the GREAT-ER 3.0 poster(PDF-format)

    • Applications

      GREAT-ER is a tool to study the impact of chemicals emitted by point sources into rivers by calculating GIS-based equivalents of 'PEClocal' and 'PECregional' for the aquatic environment.  It is most suited for modelling chemicals that are emitted down the drain from wide dispersive consumer use, or from defined point sources such as waste water treatment plants, or industrial production plants (Fig. 2).  Its use for modelling the exposure of ingredients of detergents, personal care products and pharmaceuticals is well documented [2, 3].
      An add-on Sediment Module for GREAT-ER was developed in 2006 in order to not only predict concentrations of chemicals in the water, but also in the river sediment phase. It derives per stretch the sediment concentrations based on equilibrium partitioning. GREAT-ER can also be linked with the ‘TERRACE’ Model ( ) which allows to include diffuse emissions to the river via agricultural run-off.
       GREAT-ER is currently implemented for a variety of European river basins: 5 in the UK (Aire, Calder, Went, Rother, Exe), 1 in Italy (Lambro), 6 in Germany (Itter, Unter-Main, Main, Rur, Rhine in Northrhine Westfalia, and Elbe), 1 in Belgium (Rupel), 1 in France (Mayenne), 1 in Spain (Llobregat) and 1 in Switzerland (Glatt).  The applicability of the model is generic and not limited to European river basins.

    • Software Versions

      GREAT-ER Desktop 3.0 CD (2011) Fig. 3: GREAT-ER Desktop 3.0 CD (2011)

      General principle of GREAT-ER data preprocessing Fig. 4: General principle of GREAT-ER data preprocessing

      The most current version is GREAT-ER 3.0 Desktop (2011), designed for Microsoft Windows® XP and 7 (Fig. 3). The entire system is based on open source software and can be installed without any licence fees under the GNU Public Licence. In addition the pre-processing (Fig. 4) is now available under MS Windows® XP and 7 as well. As for version 2.0, its development was sponsored by the CEFIC-Long Range Research Initiative (LRI – ).

    • References

      • Cunningham, V.L. et al. (2009). Human health risk assessment from the presence of human pharmaceuticals in the aquatic environment.  Reg. Tox. Pharmacol., 53, 39-45.
      • Pistocchi, A. et al. (2012). Continental scale inverse modelling of common organic water contaminants in European Rivers. Env. Pollut. 162, 159 – 167.
      • Gevaert, V. et al. (2009).  Evaluating the usefulness of dynamic pollutant fate models for implementing the EU Water Framework Directive. Chemosphere, 76,  27-35.
      • Pistocchi, A. et al. (2010).  Spatially explicit multimedia fate models for pollutants in Europe; state of the art and perspectives. Chemosphere 18, 3817-3830.  
      • Koormann, F., et al. (2005). Modeling the fate of down-the-drain chemicals in rivers: an improved software for GREAT-ER.  Env. Modelling & Software, 21, 925-936.
      • Feijtel, T., Boeije, G., Matthies, M., Young, A., Morris, G., Gandolfi, C., Hansen, B., Fox, K., Holt, M., Koch, V., Schroeder, R., Cassani, G., Schowanek, D., Rosenblom, J, and Niessen, H. (1997).  Development of a geography-referenced regional exposure assessment tool for European rivers - GREAT-ER. Contribution to GREAT-ER #1.  Chemosphere 34, 2351-2374.

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Illustrations from P&G's Science-in-the-Box website can be used freely for educational, non-commercial purposes provided that the source will be published as follows: "Obtained from (P&G website)"


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