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Watershed Planning within a Quantitative Scenario Analysis Framework
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Integrated data-driven cross-disciplinary framework to prevent chemical water pollution.

Mohamed Ateia1,2, Gabriel Sigmund3,4, Michael J Bentel5

  • 1United States Environmental Protection Agency, Center for Environmental Solutions & Emergency Response, Cincinnati, OH 45220, USA.

One Earth (Cambridge, Mass.)
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Summary

This study proposes an integrated, data-driven framework to address chemical water pollution by connecting chemical innovation with water treatment. It aims to foster proactive solutions and reduce societal costs associated with emerging contaminants.

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Area of Science:

  • Environmental Science
  • Chemical Engineering
  • Data Science

Background:

  • Chemical innovation and water treatment experts often work in isolation, hindering effective management of emerging contaminants.
  • A fragmented, reactive approach to chemical pollution results in significant societal costs.
  • Current methods lack connectivity between chemical life cycle stages and water remediation technologies.

Purpose of the Study:

  • To propose an integrated, data-driven framework for proactive management of chemical water pollution.
  • To enhance expert capabilities and foster novel, co-beneficial approaches across scientific domains.
  • To bridge the gap between upstream chemical innovation and downstream water treatment solutions.

Main Methods:

  • Developing a data-driven framework integrating chemical life cycle and water treatment domains.
  • Promoting open and FAIR (findable, accessible, interoperable, reusable) data practices.
  • Establishing common knowledge bases and platforms for interdisciplinary collaboration.

Main Results:

  • The framework enhances expert capabilities and facilitates novel approaches with cross-domain co-benefits.
  • It fosters proactive strategies for addressing chemical water pollution.
  • Implementation requires concerted efforts in data sharing and platform development.

Conclusions:

  • An integrated, data-driven framework is essential for effectively managing chemical water pollution.
  • Adopting open data practices and common knowledge platforms are key to operationalizing the framework.
  • Proactive, collaborative approaches can mitigate societal costs and improve ecosystem health.