Science Inventory

Integrated data-driven cross-disciplinary framework to prevent chemical water pollution

Citation:

Ibrahim, Mohamed Ateia, G. Sigmund, M. Bentel, John W. Washington, A. Lai, Nathaniel H. Merrill, AND Z. Wang. Integrated data-driven cross-disciplinary framework to prevent chemical water pollution. One Earth. Cell Press, Cambridge, MA, 6(8):952-963, (2023). https://doi.org/10.1016/j.oneear.2023.07.001

Impact/Purpose:

We propose Proactive framework to entail both proactively screening existing chemicals on global markets to identify potential micropollutants, and proactively design of novel benign and/or readily treatable chemicals.

Description:

Access to a clean and healthy environment is a human right and a prerequisite for maintaining a sustainable ecosystem. Experts across domains along the chemical life cycle have traditionally operated in isolation, leading to limited connectivity between upstream chemical innovation to downstream development of water-treatment technologies. This fragmented and historically reactive approach to managing emerging contaminants has resulted in significant externalized societal costs. Herein, we propose an integrated data-driven framework to foster proactive action across domains to effectively address chemical water pollution. By implementing this integrated framework, it will not only enhance the capabilities of experts in their respective fields but also create opportunities for novel approaches that yield co-benefits across multiple domains. To successfully operationalize the integrated framework, several concerted efforts are warranted, including adopting open and FAIR (findable, accessible, interoperable, and reusable) data practices, developing common knowledge bases/platforms, and staying vigilant against new substance “properties” of concern.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:08/18/2023
Record Last Revised:12/07/2023
OMB Category:Other
Record ID: 359750