The fast development of agro-biotechnologies asks for a harmonized approach in risk analysis of GMO's releases, where "risk analysis" entails the assessment, management and communication of risk. Risk assessment consists in the evaluation of the likelihood that a hazard occurs, associated with the presence of the receptor(s) in the receiving environment, and the determination of their potential degree of exposure to the hazard. The whole process has to be both science based and applied case by case, and it involves a very complicated procedure that needs to be transformed in an operational and standardized tool. Beginning in 2003, an expert group on behalf of the Italian Ministry of the Environment elaborated an Operating Model for the Environmental Risk Assessment (OMERA) mainly addressed to scientists, companies, regulators, environmentalists, and also aiming to provide the stakeholders with a scientifically correct source of information. OMERA is based on a logic scheme, moving from the assumption that the occurring of a risk, associated to the release of a GMO into the environment, is strictly related to the presence of four elements: a) source; b) diffusion factors; c) dispersal routes; d) receptors. It comprises two main components: a conceptual model represented as a flowchart and an electronic Questionnaire (eQ) driven by a relational database (Microsoft Office Access). The eQ includes sets of questions specifically formulated for each box of the flowchart that create a "decision tree" that can be followed from the source to all the components of the conceptual model. Completing the eQ leads to the identification of the potentially affected receptors and related potential effects. Within the framework of a LIFE+ project (MAN-GMP-ITA) a multidisciplinary group was formed to validate and improve this methodology. The questionnaire has been filled simulating the release of herbicide tolerant GT73 oilseed rape and insect resistant MON810 maize in different experimental areas. The results attested that OMERA allows the collection and comparison of experimental data in a standard way and at the same time leads to the identification of receptors, potential effects and related monitoring activities specifically for the case study. The experiences described in this paper have shown the potential area of improvement of OMERA to achieve a more functional Decision Supporting System (DSS) that would give a quantitative risk evaluation and the extension to commercial fields. As for OMERA, the DSS will be user-friendly and could be easily modified and adapted to specific situations i.e risk assessment of GM crop field trials.

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