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A data engineering framework for on-site end-of-life industrial operations
Citation:
Hernandez-Betancur, J., M. Martin, AND Gerardo J. Ruiz-Mercado. A data engineering framework for on-site end-of-life industrial operations. JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, 327:129514, (2021). https://doi.org/10.1016/j.jclepro.2021.129514
Impact/Purpose:
Conducting chemical risk evaluation supports stakeholders in the assessment and selection of safer and sustainable chemicals. Similarly, the amended Toxic Substances Control Act (TSCA) directives the USEPA to conduct risk evaluations of existing high-priority chemicals to determine their impact of harming the environment or human health across its life cycle stages. However, evaluating chemical risk during their end-of-life (EoL) stage is challenging due to more considerable uncertainty, less data availability, variability, waste mixtures, and the demands for proper reporting and traceability. Also, certain industrial facilities apply on-site pollution abatement operations, thereby constituting nodes of the chemical EoL stage. This work employs publicly available databases, data-driven models, and analytic hierarchy approaches to track chemicals of interest at on-site industrial pollution management operations. The framework develops pollution abatement unit (PAU) technologies and estimates their efficiencies, chemical releases, exposure media, operating expenses, and capital expenditures. The developed framework supports an automated and comprehensive EoL material flow analysis for risk assessment by connecting on-site and off-site EoL management activities. Also, it supports the development of robust data-driven models to evaluate chemicals outside current regulatory needs. The TRI Program, the Office of Pollution Prevention and Toxics (OPPT), the Office of Land and Emergency Management (OLEM), and the public can use the framework to identify potential on-site exposure scenarios; and estimate releases from industrial EoL activities. Additionally, to develop PAU technologies, estimate their efficiencies, occupational exposures, and operating expenses.
Description:
Sustainable initiatives for converting end-of-life (EoL) material flows into feedstocks would make a crucial contribution towards protecting our environment and mitigating the negative impacts of anthropogenic activities. Chemical flow analysis enables decision-makers to identify potential environmental releases and exposure pathways at the EoL stage and, therefore, improves the estimation of chemical exposure. Certain industrial facilities apply on-site pollution abatement operations, thereby constituting nodes of the chemical EoL management chain that can be evaluated and improved to enable greater circularity of materials. This work enhances and extends a recently published EoL data engineering framework by using publicly-available databases, data-driven models, and analytic hierarchy approaches to track chemicals, estimate releases, and potential exposure pathways at on-site industrial pollution management operations.
URLs/Downloads:
DOI: A data engineering framework for on-site end-of-life industrial operations
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