Hazard Assessment For Wastes using Multicriterial Methods Considering European And International Harmonized Legislation

Abstract

The objective of the study is to offer methodological instruments using multiple criteria for hazard waste assessment that will allow reproducibility of value judgments made by experts/specialists in the field when making such decisions based on harmonized national, European, and international legislation. In the hazard waste assessment world practice exist different methods. We will present the practice of decisional logical schemes and decisional rules derivation using multiple criteria in order to make transparent the decisional act of assessment/classification in each jurisdiction to harmonize the waste management and eventually to make possible some actions to be automated for speeding up the final decision. The proposed methodologies developed by INCD-ECOIND respond to the current legislation requirements and address the needs of scientific waste assessment and management with intend to valorize the results in the form of advanced environmental services. The proposed methodologies are based on relevant criteria like hazardous properties by waste’s origin (i.e. waste existing on relevant waste lists - coming from different specific technological processes etc.) and hazardous properties by waste’s composition (i.e. based on results of relevant performed tests revealing hazardous properties for certain components of the analyzed waste from beneficiaries). Information about the analyzed waste has been obtained from beneficiaries, from literature and from INCD-ECOIND performed analytical determinations (over 12 relevant indicators). The classification results are finally presented. The proposed multiple criteria type of methodologies offer efficient, short, logic, and mathematical algorithms for data reduction and discovery of relevant decision rules within the available data information. They offer easy interpretation of the obtained results, revealing the quality of classification, allowing the automation of some actions but also manual (pre)processing of data depending on situation, in order to support the final classification decision.