Best Available Techniques: An integrated method for multicriteria assessment of reference installations

Abstract : The Industrial Emission Directive (IED) has strengthened the requirement to apply Best Available Techniques (BATs) first introduced by the IPPC Directive. The so-called “Sevilla Process”, which is the formal European process to define and revise BATs, is based upon an exchange of information among different stakeholders and relies on data analysis and expert judgements. If the process to collect and to share information between stakeholders at sectoral and installation levels is well defined, the determination of BATs and BAT-Associated Environmental Levels has evolved along with the revision of the BAT REFerence documents (BREFs). Nevertheless, no formal tool to support the analysis exists. The objective of this article is to present a 5-steps methodology aimed to classify installations according to two multicriteria approaches, either a representative angle or a performant approach, and then to identify reference installations, which would help to propose reference values and possible BATs. The methodology is supported by statistical tools (Principal Component analysis, hierarchical clustering) and algorithmic approach (MissForest). The application to French dairy sectors has validated the methodology and mathematical tools used. Two reference classes has been identified for the representative approach and 19 installations selected. For the performant installations, seven (7) installations has been selected. BATAELs for COD flow are proposed considering these classifications and an effort rate comprised between 23 and 96% has been revealed.
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Journal articles
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https://hal-emse.ccsd.cnrs.fr/emse-01955003
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Submitted on : Friday, December 14, 2018 - 10:11:50 AM
Last modification on : Tuesday, November 19, 2019 - 2:37:53 AM

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Damien Evrard, Jonathan Villot, Chadad Armiyaou, Rodolphe Gaucher, Sofia Bouhrizi, et al.. Best Available Techniques: An integrated method for multicriteria assessment of reference installations. Journal of Cleaner Production, Elsevier, 2018, 176, pp.1034-1044. ⟨10.1016/j.jclepro.2017.11.234⟩. ⟨emse-01955003⟩

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