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  • Quantitative Risk Assessment (QRA)

    A key element for dimensioning an environmental problem

    Risk Analysis

    Whenever the presence of potential contaminants is detected on a piece of land, alarms ring and it is necessary to answer some core questions:

    Does it imply a non-acceptable risk for humans or ecosystems?
    Is it necessary to take any action?
    Which legal matters should be considered?

    The first step to resolve all these questions is to determine the severity of the affection by contaminants in the site and its extension, the potential mobilization, the kind of activities that are developed within this site, and the characteristics of the surroundings. Once this first approach of the situation is completed, LITOCLEAN develops a conceptual model of the specific emplacement and, based upon it, evaluates the potential risk to which human and ecological receptors are exposed, through a Quantitative Risk Assessment (QRA). 

    This allows to determinate if the affection implies an unacceptable situation and, in this case, if it is required to implement a remediation plan or to adopt other corrective actions.

    This work results of great value for many agents, specially:

    - The industry, in different phases of its operation, since its baseline report, to the definition of actions to adopt in response to an accidental spillage or escape of contaminants, the renewal of concessions, as part of a Due Diligence, etc.

    - Real state, making easier the process of the pricing of a property, through the knowledge of the environmental quality of its soil, according to its actual or planned use in the future.

    - Community, since it provides information about the environmental status of places of public interest. 

    LITOCLEAN has been a pioneer in Spain in the use of simulation for risk calculations and, living up to that spirit, today it figures amongst the first Spanish consultants to obtain the ENAC accreditation in the field of risk assessments. The company commits to excellence standards in the execution of QRA, knowing that its conclusions are key to dimension a problem and optimize the use of resources in its resolution.