New Research Framework Balances Water Conservation and Carbon Reduction in Chinese Industry

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. The mechanism-data dual-driven approach combines hybrid modeling of water-use and treatment processes with superstructure optimization to identify optimal pathways for industrial water network optimization.

Yuehong Zhao and Hongbin Cao from the Institute of Process Engineering of Chinese Academy of Sciences created the framework to solve the complex water-carbon-economy nexus problem facing Chinese industry. The research, detailed in the study published in Water & Ecology (doi:https://doi.org/10.1016/j.wateco.2025.100003), integrates mechanistic understanding of water processes with data-driven techniques to enhance model interpretability and generalization capabilities even with limited training datasets.

The hybrid modeling approach builds on deep understanding of typical water-use, wastewater treatment, and reuse processes within industrial parks. By combining mechanistic knowledge with machine learning and AI technologies, the framework represents an effective method for promoting advanced computational techniques in the industrial sector. However, the researchers note that systematic theory and methodology for hybrid modeling remain underdeveloped, with key challenges including how to select appropriate mechanisms and their expressions for integration with machine learning.

The superstructure optimization model constructed as part of the framework encompasses 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, the researchers established a multi-scale optimization methodology for water conservation in industrial parks, leading to the development of practical software tools successfully applied in steel companies.

The framework's effectiveness in balancing economic and environmental benefits has been confirmed through case studies. As Zhao explains, "By solving the obtained optimization model, the optimal technical pathway for simultaneous water conservation and carbon emission reduction at a minimum water-use cost can be identified. It provides valuable information to support the decision-making about water network optimization within industrial parks."

The research, supported by a grant from the key Program of National Natural Science Foundation of China (51934006), offers significant implications for industrial sustainability. According to Cao, "The framework can provide a solution which balances local and overall benefits, as well as economic benefits and environmental impacts." This approach represents a crucial advancement in addressing the interconnected challenges of water scarcity, carbon emissions, and ecological preservation in industrial settings, potentially serving as a model for similar applications worldwide. The original research is available at https://doi.org/10.1016/j.wateco.2025.100003.