TY - JOUR AU - Aboagye, Emmanuel A. AU - Pimentel, Jean AU - Orosz, Ákos AU - Cabezas, Heriberto AU - Friedler, Ferenc AU - Yenkie, Kirti M. PY - 2021/11/15 Y2 - 2024/03/29 TI - Efficient Design and Sustainability Assessment of Wastewater Treatment Networks using the P-graph Approach: A Tannery Waste Case Study JF - Chemical Engineering Transactions VL - 88 SP - 493-498 SE - Research Articles DO - 10.3303/CET2188082 UR - https://www.cetjournal.it/index.php/cet/article/view/CET2188082 AB - In the tannery industry approximately, 30 - 35 m3 of wastewater (WW) is generated per ton of rawhide processed. The WW comprises high concentrations of salts, ammonia, dye, solvents, and chromium. Of particular interest is chromium, which has been proven to cause dermatological, developmental, and reproductive issues on exposure. Thus, there is a need for appropriate treatment of the tannery WW before it is discharged for natural remediation. However, designing a treatment process is multifaceted due to the availability of multiple technologies that can perform similar tasks and the complex composition of waste streams. This necessitates the treatment to be performed in stages namely, primary, secondary, and tertiary. In some cases, pretreatment is required to enhance the recovery in the following stages. Due to the combinatorial nature of this problem, the P-graph approach, which uses principles from graph theory, can be used to synthesize a treatment pathway by selecting appropriate technologies at each stage, while meeting required purity specifications. Furthermore, the P-graph approach can provide alternate feasible treatment structures ranked based on Economics as well as Sustainability indicators, such as the Sustainable Process Index (SPI). In this work, a tannery WW case study is investigated with multiple stages and treatment technologies. A complex maximal structure is generated comprising all possible technologies, flows, connections, bypasses, mixers, and splitters. The models for each technology involve capital and operating costs, efficiency, and SPI at each stage of the treatment process. This problem is formulated in P-graph and solved using the Accelerated Branch-and-Bound algorithm. ER -