Carbon Emissions Analysis by AI Techniques

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 101

Special Issue Editors

College of Architecture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Interests: AI-driven method; data mining; big data; energy efficiency; urban carbon emissions; energy prediction

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Guest Editor
Department of the Built Environment, National University of Singapore, Singapore 117566, Singapore
Interests: machine learning; building simulation; building energy management; optimal control; smart building
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Special Issue Information

Dear Colleagues,

In the face of escalating global concern over carbon (CO2) emissions and their impact on climate change, innovative solutions are paramount for societies of all sizes. The advent of artificial intelligence (AI) offers transformative potential to address these challenges, marking a pivotal shift in applied energy research. This Special Issue delves into the cutting-edge intersection of AI-driven technologies and carbon emissions efficiency, showcasing pioneering research and methodologies aimed at a sustainable, low-carbon future.

Despite the promising horizon, the application of AI, machine learning, and related technologies in carbon emissions evaluation and forecasting faces notable research gaps. By bringing together the latest in AI-related technologies—including machine learning, data mining, time series analytics, data-driven prediction and forecasting, the Internet of things (IoT), sensor networks, and cutting-edge computing—this Special Issue aims to chart a course toward actionable interpretable data-driven strategies for energy conservation, optimal clean energy utilization, and significant reductions in carbon emissions. This Special Issue serves as a platform for exchanging high-quality research findings, innovative solutions, and discussions that bridge these gaps. It encourages submissions that leverage data-driven techniques with a focus on enhancing interpretability, efficiency, and effectiveness in carbon emissions analytics, modeling, and forecasting.

This Special Issue highlights a spectrum of topics central to this discourse, including, but not limited to: AI-driven smart energy savings, energy efficiency and management, carbon emissions and energy forecasting, machine learning and big data analytics, smart urban development with clean energy, and energy modeling as well as optimization. Each topic represents a facet of the comprehensive approach required to tackle the multifaceted challenges of the reduction in carbon emissions and energy management in the 21st century.

Best regards,

Dr. Tian Li
Dr. Sicheng Zhan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Information 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 1600 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.


  • AI-driven energy analysis
  • carbon emissions and energy forecasting
  • machine learning and big data analytics
  • energy efficiency and management
  • smart urban development with clean energy
  • energy modeling and optimization

Published Papers

This special issue is now open for submission.
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