Industrial facilities might release many chemical substances during the production of value-added products. These chemical releases may cause damage to a receptor, either occupational and non-occupational population, and the environment. Therefore, to determine whether a chemical poses a considerable risk to human health and the environment, several tasks must be completed. These include determining the releases to the environment from conditions of use. Therefore, this work aims to develop a process-oriented, decision-making, and learning-from-data framework which integrates: (a) estimation of chemical releases from an industrial facility taking into consideration the type of processes, the condition of use, and the physical-chemical properties of a substance; (b) environmental sustainability indicators based on U.S. Environmental Protection Agency (USEPA)âs GREENSCOPE; (c) a decision-making procedure based on fuzzy techniques to include stakeholdersâ opinions; and (d) an aggregation method to incorporate the existing trade-off between the USEPAâs GREENSCOPE environmental indicators. A case of study for the U.S. metal coating industry is employed for applying the proposed framework as a tool for supporting environmental decision-making efforts and chemical release minimization. In addition, this framework may be suitable for chemical risk evaluation and environmental sustainability decision-making for industrial systems.
The views expressed in this abstract are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.