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Analysis of Environmental Distribution, Mechanisms of Effects, and Risk of Pollutants Driven by New Technologies

This special issue belongs to the section “Novel Methods in Toxicology Research“.

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) and machine learning (ML) algorithms (such as deep learning and random forests) deeply explore complex correlations and patterns in massive eDNA, omics data, and traditional monitoring data to precisely map the dynamic spatiotemporal distribution of pollutants across multiple media, identify migration and transformation hotspots, construct predictive models (such as QSAR), and analyze their toxic effects. Based on this, risk assessment and management have entered a brand-new AI era.

With this in mind, this Special Issue will provide updated insights into the application of new technologies in environmental pollutants. Topics of interest include environmental distribution, health effects, and risk management, with a particular focus on emerging pollutants and priority pollutants.

We invite pioneering scientists to submit their work to this Special Issue. Research articles, reviews, perspectives, commentary, etc., providing evidence on how to use new technologies to conduct pollutant research are welcome.

Prof. Dr. Zhen-Guang Yan
Dr. Yizhang Zhang
Dr. Yifan Zheng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Toxics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • machine learning
  • environmental DNA
  • emerging pollutants
  • optimal control pollutants
  • environmental omics
  • risk assessment
  • risk management

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Toxics - ISSN 2305-6304