Modeling Sustainable Processes—Aiming Towards Decarbonization in the Era of Artificial Intelligence

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Chemical Processes and Systems".

Deadline for manuscript submissions: closed (30 November 2025) | Viewed by 2785

Editors


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Guest Editor
Department of Chemical Engineering, Izmir Institute of Technology, Gülbahçe Campus, Urla, Izmir 35430, Turkey
Interests: computational fluid dynamics (CFD) of reactor and process design; reactor engineering; process intensification; energy-efficiency in reactor design for process intensification
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Guest Editor
Department of Chemical Engineering, Izmir Institute of Technology, Gülbahçe Campus, Urla 35430, Izmir, Turkey
Interests: Machine Learning; Process Automation; Mixed-integer Programming; Optimization

Special Issue Information

Dear Colleagues,

The 21st century presents an urgent challenge: decarbonizing our processes to combat climate change. As industries seek sustainable transitions, artificial intelligence (AI) stands out as a powerful tool. By optimizing energy use, streamlining industrial operations, and supporting the integration of renewable power, AI offers concrete pathways to reduce emissions at a large scale. From digital twins to intelligent simulations, AI enables the modeling of low-carbon processes across sectors such as chemical, petrochemical, food, bitechnology, and agricultural industries. These tools are not just theoretical; they are essential for transforming systems and accelerating the shift toward a carbon-neutral economy.

The MaCKiE conference offers a vital platform at this intersection of modeling, computation, and the knowledge economy. In the context of decarbonization, MaCKiE brings together researchers, industry leaders, and policymakers to share innovations, frameworks, and real-world applications that advance AI-driven sustainability. This Special Issue will support MaCKiE 2025 and welcomes studies on sustainable processes that we can achieve through decarbonization in the era of artificial intelligence.

Dr. Abhishek Dutta
Dr. Hasan Sildir
Guest Editors

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Keywords

  • process dynamics
  • mathematical modeling
  • process integration and optimization
  • chemical and biological processes
  • artificial intelligence
  • big data
  • sustainability

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Published Papers (1 paper)

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Review

26 pages, 2243 KB  
Review
A Study of the Environmental Challenges En Marche Towards Net-Zero: Case Study of Turkish Steel Industry
by Ateş Batıkan Özdamar, Miray Kaya, Abdulkadir Bektaş, Srijita Bhattacharyya, Mert Şahindoğan, Jean-Pierre Birat and Abhishek Dutta
Processes 2026, 14(1), 178; https://doi.org/10.3390/pr14010178 - 5 Jan 2026
Cited by 1 | Viewed by 2220
Abstract
The Turkish steel industry aims to reduce its sectoral carbon dioxide (CO2) emissions by 55% by 2030, in line with Türkiye’s Paris Agreement commitments and the European Green Deal (EGD), and consistent with the ambition of the European Union’s economy-wide ‘Fit [...] Read more.
The Turkish steel industry aims to reduce its sectoral carbon dioxide (CO2) emissions by 55% by 2030, in line with Türkiye’s Paris Agreement commitments and the European Green Deal (EGD), and consistent with the ambition of the European Union’s economy-wide ‘Fit for 55’ emissions-reduction target. Türkiye faces significant challenges in achieving net-zero greenhouse gas (GHG) emissions, particularly as a developing country confronting the impacts of climate change and in the market situation, such as the effects of the ongoing Russia-Ukraine conflict, limited access to affordable raw materials, and rising operational costs. This study serves as a guideline for the Turkish steel sector’s roadmap towards modernization and eventual compliance with net-zero targets. The consideration and integration of new technologies planned for the Turkish steel industry, in both electric arc furnace (EAF) and blast furnace-basic oxygen furnace (BF-BOF) facilities, have been outlined in conjunction with green hydrogen and with Carbon Capture and Storage (CCS) technologies. Four different scenarios were analysed to understand the reduction in CO2 emissions: (1) In a Business-As-Usual (BAU) scenario without any reduction, (2) 39.9% CO2 emission reduction with the Moderate scenario, (3) 59.6% reduction with the Advanced scenario, and (4) 82.9% reduction in CO2 emissions from the Turkish steel sector with the Net-Zero scenario. To quantify the uncertainty in these long-term projections, a Monte Carlo simulation was conducted, generating probabilistic confidence intervals that reinforce the robustness and credibility of the net-zero pathway. The official roadmap for the sector is not available as of today; however, an in-depth discussion with a policy innovation leading to it is the objective of this study. Full article
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