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 716
Special Issue Editors
Interests: AI-driven method; data mining; big data; energy efficiency; urban carbon emissions; energy prediction
Interests: machine learning; building simulation; building energy management; optimal control; smart building
Special Issues, Collections and Topics in MDPI journals
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 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 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 1800 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
- 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
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
