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Air micro-pollutants analysed through rough set approach

Air micro-pollutants analysed 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 particularly 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. Keywords: industrial areas; air pollution; meteorological attributes; RSA; rough set approach. Reference to this paper should be made as follows: Matarazzo, A. (2016) `Air micro-pollutants analysed through rough set approach', Progress in Industrial Ecology ­ An International Journal, Vol. 10, No. 4, pp.382­397. Biographical notes: Agata Matarazzo is an http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Progress in Industrial Ecology, an International Journal Inderscience Publishers

Air micro-pollutants analysed through rough set approach

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Publisher
Inderscience Publishers
Copyright
Copyright © 2016 Inderscience Enterprises Ltd.
ISSN
1476-8917
eISSN
1478-8764
DOI
10.1504/PIE.2016.083925
Publisher site
See Article on Publisher Site

Abstract

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 particularly 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. Keywords: industrial areas; air pollution; meteorological attributes; RSA; rough set approach. Reference to this paper should be made as follows: Matarazzo, A. (2016) `Air micro-pollutants analysed through rough set approach', Progress in Industrial Ecology ­ An International Journal, Vol. 10, No. 4, pp.382­397. Biographical notes: Agata Matarazzo is an

Journal

Progress in Industrial Ecology, an International Journal – Inderscience Publishers

Published: Jan 1, 2016

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