A new research framework developed by Chinese scientists addresses the critical challenge of balancing water conservation, carbon emission reduction, and aquatic ecosystem preservation in China's industrial sector while minimizing costs. Researchers Yuehong Zhao and Hongbin Cao from the Institute of Process Engineering of Chinese Academy of Sciences proposed a mechanism-data dual-driven approach that combines traditional engineering understanding with modern data analysis techniques.
The framework involves developing hybrid models to characterize water-use and treatment processes along with their associated carbon emissions. According to Zhao, the lead author of the study published in Water & Ecology, solving the optimization model identifies the optimal technical pathway for simultaneous water conservation and carbon emission reduction at minimum water-use cost. The research provides valuable information to support decision-making about water network optimization within industrial parks, as detailed in their publication available at https://doi.org/10.1016/j.wateco.2025.100003.
The hybrid modeling approach integrates mechanistic understanding with data-driven techniques, enhancing model interpretability and generalization even with limited training datasets. This represents an effective approach to promoting the application of machine learning and AI technologies in the industrial sector. However, Cao notes that systematic theory and methodology for hybrid modeling remain underdeveloped, with key challenges including how to select the appropriate mechanism and its expression for integration with machine learning.
A superstructure optimization model was constructed based on unit models and domain knowledge, encompassing feasible unit technologies, their interconnections, and relevant constraints to identify optimal solutions. Deterministic optimization algorithms were applied to achieve global optimum solutions with minimal water-use cost. In case studies, researchers established a multi-scale optimization methodology for water conservation in industrial parks, leading to the development of a practical software tool successfully applied in steel companies.
The framework's significance lies in its ability to provide solutions that balance local and overall benefits, as well as economic benefits and environmental impacts. This approach comes at a critical time when Chinese industry faces increasing pressure to meet environmental targets while maintaining economic viability. The research was supported by a grant from the key Program of National Natural Science Foundation of China (51934006), demonstrating the national importance of developing sustainable industrial water management solutions.
