(58o) A Techno-Economic Model and Decision-Making Matrix for Wastewater Biosolids Reuse Application

Background Biosolids is a massive by product stream leaving wastewater treatment plants and water management facilities worldwide. While biosolids have been considered as a waste by-product that has been landfilled for decades, recent research in the area proved that they can be considered a valuable asset due to their content of nutrients and energy(Wang et al., 2008; Zhao et al., 2019) .They are now officially defined as renewable source of energy due to the energy value of their organic content (Edwards et al., 2017; Egan, 2013) . Biosolids management and reuse strategies for energy generation exhibit a high potential for achieving circular economy and minimizing wastes to the environment (Egan, 2013). Biosolids potential mass and energy recovery applications include land fertilization, composting, anerobic digestion, combustion, gasification, pyrolysis, and hydrothermal treatment. Through these applications biosolids are converted into valuable nutrient source such as composts or energy sources such as biofuels and char. Each of these applications requires a specified initial pretreatment to condition the biosolids stream. Treatment of biosolids has been reported as one of the major challenges in water management and treatment plants as the electricity and operational cost associated to the process accounts for 20% and 53% of the overall treatment process of wastewater (Zhao et al., 2019).

Motive And Objective There are various factors dictating the suitability of an application for biosolids reuse. These factor ranges from the characteristics of the biosolids stream, targeted products, the technical limitations on the application such as capacities, percentage of moisture or availability of utilities, cost parameters and environmental and societal factors. The available literature provides abundance of information on different reuse applications and their expected output but it lacks clear guidance on how to make the decision on which application is most suitable for a given biosolids feed from both technical and economical point of view. This project aims at creating a robust model and a decision-making matrix for the selection of the most suitable application to treat a given biosolid stream. The model targets maximizing material and energy recoveries from the biosolids while minimizing the energy and equipment costs involved as well as environmental emissions.

Methodology A techno economic model to evaluate net energy, cost and emission associated with the treatment of biosolids steam is being developed. The model provides a decision-making tool on what is the optimum application to be implemented for a stream of biosolids. The calculation model is a mixed integer linear programming MILP model. Model inputs include flowrate and composition of biosolids stream, and cost parameters. Binary variables are defined. Mass and Energy balances and application limitations are used to define the constraints on the model. One of the main objective functions is the cost minimization function. The figure attached shows a sample illustrative representation of the model and the generic cost minimization equation that represent it. Python codes are being developed to solve the set of equations and provide the optimized solution to enable decision making by the user.

References:

Edwards, J., Othman, M., Crossin, E., & Burn, S. (2017). Anaerobic co-digestion of municipal food waste and sewage sludge: A comparative life cycle assessment in the context of a waste service provision. Bioresource Technology, 223, 237–249. https://doi.org/10.1016/j.biortech.2016.10.044

Egan, M. (2013). Biosolids management strategies: An evaluation of energy production as an alternative to land application. In Environmental Science and Pollution Research (Vol. 20, Issue 7, pp. 4299–4310). https://doi.org/10.1007/s11356-013-1621-1

Wang, H., Brown, S. L., Magesan, G. N., Slade, A. H., Quintern, M., Clinton, P. W., & Payn, T. W. (2008). Technological options for the management of biosolids. In Environmental Science and Pollution Research (Vol. 15, Issue 4, pp. 308–317). https://doi.org/10.1007/s11356-008-0012-5

Zhao, G., Garrido-Baserba, M., Reifsnyder, S., Xu, J. C., & Rosso, D. (2019). Comparative energy and carbon footprint analysis of biosolids management strategies in water resource recovery facilities. Science of the Total Environment, 665, 762–773. https://doi.org/10.1016/j.scitotenv.2019.02.024