This Special Issue will focus on the latest advances on the intersection of machine learning (ML) and artificial intelligence (AI) in the translation and utilization of outputs from sensor and measurement systems in atmospheric chemistry and climate research. Submit your manuscript by January 29, 2025.

An image of the earth in space.

The climate and atmospheric chemistry communities have petabyte-sized data sets and petaflops of computing power. Joining and translating the outputs from the myriad sensor, measurement, and modeling systems to meaningful predictions of a relevant size and time scale are key next steps to enable us to answer operationally relevant questions in real time. The use of machine learning (ML) and artificial intelligence (AI) methods and their intersection with measurements and modeling as it relates to understanding air chemistry and climate changes and mitigation challenges is the focus of this Special Issue in ACS ES&T Air.

This Special Issue is seeking a broad range of contributions on all aspects of the use of machine learning and artificial intelligence in air chemistry and climate modeling and measurements. Papers focusing on everything from atmospheric chemistry measurements on specific problems, to the pairing of large data sets with ML and AI tools to address specific problems and mitigation strategies are welcome.

Topics include, but are not limited to:

  • Atmospheric chemistry measurements that relate to specific problems at an operational level
  • Models of atmospheric and climate processes that provide sufficient resolution to address specific needs and outcomes. Examples include precipitation prediction, heat indexing, pollution, etc.
  • The use of ML and AI to address filter the extremely large data sets and pair the relevant data with appropriate problems.

This call for papers is in collaboration with the ACS Committee on Science Symposium entitled ‘Elevating Atmospheric Chemistry Measurements and Modeling with Artificial Intelligence’ at the 2024 ACS Fall National Meeting in Denver, Colorado, United States. The Symposium is jointly sponsored by the AGRO, ANYL, CES, CINF, ENVR, GEOC, PHYS, and PRES divisions of the American Chemical Society.

Organizing Editors

Prof. Sam Silva, Guest Editor, ACS ES&T Air
University of Southern California, United States

Prof. Mathew Evans, Guest Editor, ACS ES&T Air
University of York, United Kingdom

Prof. Nga Lee (Sally) Ng, Editor-in-Chief, ACS ES&T Air
Georgia Institute of Technology, United States

Submission Information

We welcome submissions for this Special Issue through January 29, 2025. For more information on submission requirements, please visit the journal’s author guidelines page.

Accepted manuscripts for consideration in this Special Issue includes all article types (research articles, review, perspectives, feature, policy analysis and viewpoints). Papers accepted for publication for this Special Issue will be available ASAP (as soon as publishable) online as soon as they are accepted. After all submissions have been published, they will then be compiled online on a dedicated landing page to form the Special Issue. Manuscripts submitted for consideration will undergo the full rigorous peer review process expected from ACS journals.

How to Submit

  • Log in to the ACS Paragon Plus submission site.
  • Choose ACS ES&T Air.
  • Select your manuscript type, and, under "Special Issue Selection," choose “Elevating Atmospheric Chemistry Measurements and Modeling with Artificial Intelligence.”

If you have any general questions regarding submission to this Special Issue, please contact the journal's managing editor.

Open Access

There are diverse open-access options for publications in American Chemical Society journals. Please visit our Open Science Resource Center for more information.

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