Air Micro-Pollutants Analyzed Through Rough Set Approach

This study presents a rough set application to air micro-pollution management in an industrial site with a high environmental risk rate. This new data analysis tool is able to deal both with quantitative and qualitative data, and the results are expressed in terms of understandable decision rules. Therefore, it could be efficiently used for supporting the environmental management and particullaly pollution risk. In this paper, we present some issue related to multi-attribute. preference ordered classification of air pollution risk, considering some meteorological variables as attributes and criteria describing the different objects (pollution occurrences), i.e., levels of particular pollutants. After recalling some methodological basic concepts, the most significant results obtained are presented and discussed: examples of decision rules, attribute relevance, exchangeable or indispensable attributes/criteria, interaction between them. Moreover, we underline that the decision rules obtained can also be usefully implemented in order to efficiently manage the risk of air pollution