(218b) Sustainability and Economic Evaluation of Tannery Wastewater Treatment Pathways Using the P-Graph Approach

The growth in world population has increased the pressure on freshwater demand. One of the mitigation approaches to meet this growing demand is wastewater treatment (Alasino et al., 2007; Crini and Lichtfouse, 2019; Inc et al., 2002). However, the treatment of wastewater for reuse must be given a holistic view by incorporating the techno-economic analysis and sustainability assessment simultaneously (Yenkie, 2019). The often-conflicting views of economics and sustainability associated with industrial processes can be bridged through the application of optimization methods.

The tannery industry is a major source of wastewater. It is important to treat it carefully due to the presence of high levels of contaminants, especially chromium. Treated tannery wastewater is beneficial for irrigation purposes due to the presence of nitrogen, phosphorus, potassium, and organic matter (Saxena and Bharagava, 2016). The stagewise treatment of wastewater presents a viable way of capturing all the complexities associated with the process.

The objective of this work is to provide multiple feasible pathways to tannery wastewater treatment by quantifying simultaneously the economics and sustainability. This is achieved by developing an Excel-based P-graph tool that gives the n-best feasible pathways ranked from least to highest based on cost and sustainability metrics.

In this work, treatment technologies were categorized into stages based on their efficiencies, driving forces for contaminant removal, and composition of wastewater. Further, due to the difference in efficiencies of technologies within a stage, treatment options of higher efficiency were preceded by options with lower efficiency. Through this approach, a maximal treatment structure was generated. Economic models were incorporated consisting of investment and operating costs. The sustainable process index (SPI), which has been used extensively to assess the ecological footprint of industrial processes was used as the sustainability metric (Krotscheck and Narodoslawsky, 1996; Narodoslawsky, 2015; Narodoslawsky and Krotscheck, 2004). The SPI methodology was used to evaluate the total area needed to provide a unit (1m³) amount of treated wastewater. There are seven footprints associated with the SPI methodology which can be categorized into two broad areas, namely input and output. Input areas account for the resources that are consumed by the process while the output indicates that needed to embed products and emissions into the ecosphere. The P-graph approach, a graph-theoretic framework for the synthesis and optimization of process networks, was implemented by developing an Excel-based realization of software (Cabezas et al., 2018; Friedler et al., 1993; Heckl et al., 2010; Yenkie et al., 2021). The optimization problem was solved formulating a mixed-integer linear programming problem and employing the accelerated Branch-n-bound algorithm in the Excel-based P-graph tool. Figure 1 summarizes our scope of work for the tannery wastewater case study.

References

Alasino, N., Mussati, M.C., Scenna, N., 2007. Wastewater Treatment Plant Synthesis and Design. Ind. Eng. Chem. Res. 46, 7497–7512. https://doi.org/10.1021/ie0704905

Cabezas, H., Argoti, A., Friedler, F., Mizsey, P., Pimentel, J., 2018. Design and engineering of sustainable process systems and supply chains by the P-graph framework. Environ. Prog. Sustain. Energy 37, 624–636. https://doi.org/10.1002/ep.12887

Crini, G., Lichtfouse, E., 2019. Advantages and disadvantages of techniques used for wastewater treatment. Environ. Chem. Lett. 17, 145–155. https://doi.org/10.1007/s10311-018-0785-9

Friedler, F., Tarjan, K., Huang, Y.W., Fan, L.T., 1993. Graph-theoretic approach to process synthesis: Polynomial algorithm for maximal structure generation. Comput. Chem. Eng. 17, 929–942. https://doi.org/10.1016/0098-1354(93)80074-W

Heckl, I., Friedler, F., Fan, L.T., 2010. Solution of separation-network synthesis problems by the P-graph methodology. Comput. Chem. Eng., Selected Paper of Symposium ESCAPE 19, June 14-17, 2009, Krakow, Poland 34, 700–706. https://doi.org/10.1016/j.compchemeng.2010.01.019

Inc, M.& E., Tchobanoglous, G., Burton, F.L., Stensel, H.D., 2002. Wastewater Engineering: Treatment and Reuse, 4th edition. ed. McGraw Hill Higher Education, Boston.

Krotscheck, C., Narodoslawsky, M., 1996. The Sustainable Process Index a new dimension in ecological evaluation. Ecol. Eng. 6, 241–258. https://doi.org/10.1016/0925-8574(95)00060-7

Narodoslawsky, M., 2015. Chapter 3 - Sustainable process index, in: Klemeš, J.J. (Ed.), Assessing and Measuring Environmental Impact and Sustainability. Butterworth-Heinemann, Oxford, pp. 73–86. https://doi.org/10.1016/B978-0-12-799968-5.00003-8

Narodoslawsky, M., Krotscheck, Ch., 2004. What can we learn from ecological valuation of processes with the sustainable process index (SPI) — the case study of energy production systems. J. Clean. Prod., Advances in cleaner production technologies 12, 111–115. https://doi.org/10.1016/S0959-6526(02)00184-1

Saxena, G., Bharagava, R.N., 2016. Organic Pollutants in Tannery Wastewater and Bioremediation Approaches for Environmental Safety 34.

Yenkie, K.M., 2019. Integrating the three E’s in wastewater treatment: efficient design, economic viability, and environmental sustainability. Curr. Opin. Chem. Eng. 26, 131–138. https://doi.org/10.1016/j.coche.2019.09.002

Yenkie, K.M., Pimentel, J., Orosz, A., Cabezas, H., Friedler, F., n.d. The P-graph Approach for Systematic Synthesis of Wastewater Treatment Networks. AIChE J. 2021 https://doi.org/10.1002/aic.17253