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Applications and Advances of Artificial Intelligence for Sustainable Environment Management and Education

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: closed (15 November 2025) | Viewed by 1602

Special Issue Editor


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Guest Editor
Department of International Business, Tunghai University, Taichung City 407224, Taiwan
Interests: artificial intelligence; environmental management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Environmental management is crucial for the future survival of humanity. In recent years, the development of artificial intelligence technologies has led to a society filled with various forms of AI. Therefore, this Special Issue aims to explore topics related to environmental management and AI, with a focus on advancing sustainability. We welcome research leveraging AI to promote sustainability, mitigate environmental impacts, and harmonize human activities with nature.

Suitable topics include, but are not limited to, the following:

  • AI application for environment management.
  • AI application for sustainable management.
  • Big data in carbon management.
  • Prediction model for climate change.
  • NLP for environmental knowledge.
  • Image classification for environmental diagnosis.
  • Big data analysis for education.
  • AI modeling of environmental behavior.
  • Data science for education in Sustainability.
  • AI-driven sustainable environmental management.

Dr. Yen-Hsun Chuang
Guest Editor

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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
  • decision support system
  • environmental monitoring
  • data mining
  • big data
  • statistic analysis
  • sustainable environmental management

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Published Papers (1 paper)

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Research

24 pages, 1132 KB  
Article
Interplay of Industrial Robots, Education, and Environmental Sustainability in United States: A Quantile-Based Investigation
by Rmzi Khalifa and Hasan Yousef Aljuhmani
Sustainability 2025, 17(22), 10255; https://doi.org/10.3390/su172210255 - 16 Nov 2025
Cited by 2 | Viewed by 1108
Abstract
This study explores the dynamic relationship between industrial robots, education, and environmental sustainability in the United States, emphasizing their role in reducing CO2 emissions. The research aims to quantify how automation, human capital, and the energy transition contribute to carbon mitigation within [...] Read more.
This study explores the dynamic relationship between industrial robots, education, and environmental sustainability in the United States, emphasizing their role in reducing CO2 emissions. The research aims to quantify how automation, human capital, and the energy transition contribute to carbon mitigation within a data-driven, AI-oriented policy framework. Quarterly data spanning 2011Q1–2024Q4 were analyzed using the advanced Quantile-on-Quantile Autoregressive Distributed Lag (QQARDL) model, which captures heterogeneous long- and short-run effects across emission distributions. Results reveal that industrial robot adoption, education, and renewable energy transition significantly reduce emissions, with the strongest effects occurring at both high- and low-emission quantiles. Economic growth and financial development also support decarbonization when complemented by green finance and innovation, while urbanization increases emissions unless aligned with compact urban design and clean energy systems. The findings imply that AI-driven industrial robotics and education jointly foster sustainability through efficiency, innovation, and awareness. Policymakers are encouraged to integrate automation strategies, renewable energy incentives, and sustainability education into climate policy. This study provides empirical evidence supporting the Resource-Based View, highlighting human capital and intelligent automation as strategic assets for achieving long-term carbon neutrality. Full article
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