A Monte-Carlo-based method for the optimal placement and operation scheduling of sewer mining units in urban wastewater networks

Ε. Psarrou, I. Tsoukalas, and C. Makropoulos, A Monte-Carlo-based method for the optimal placement and operation scheduling of sewer mining units in urban wastewater networks, Water, 10 (2), 200, doi:10.3390/w10020200, 2018.



Pressures on water resources, which have increased significantly nowadays mainly due to rapid urbanization, population growth and climate change impacts, necessitate the development of innovative wastewater treatment and reuse technologies. In this context, a mid-scale decentralized technology concerning wastewater reuse is that of sewer mining. It is based on extracting wastewater from a wastewater system, treating it on-site and producing recycled water applicable for non-potable uses. Despite the technology’s considerable benefits, several challenges hinder its implementation. Sewer mining disturbs biochemical processes inside sewers and affects hydrogen sulfide build-up, resulting in odor, corrosion and health-related problems. In this study, a tool for optimal sewer mining unit placement aiming to minimize hydrogen sulfide production is presented. The Monte-Carlo method coupled with the Environmental Protection Agency’s Storm Water Management Model (SWMM) is used to conduct multiple simulations of the network. The network’s response when sewage is extracted from it is also examined. Additionally, the study deals with optimal pumping scheduling. The overall methodology is applied in a sewer network in Greece providing useful results. It can therefore assist in selecting appropriate locations for sewer mining implementation, with the focus on eliminating hydrogen sulfide-associated problems while simultaneously ensuring that higher water needs are satisfied.

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See also: https://www.mdpi.com/2073-4441/10/2/200

Our works referenced by this work:

1. D. Koutsoyiannis, Design of Urban Sewer Networks, Edition 4, 180 pages, doi:10.13140/RG.2.1.2169.1125, National Technical University of Athens, Athens, 2011.
2. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget, Environmental Modelling and Software, 77, 122–142, doi:10.1016/j.envsoft.2015.12.008, 2016.
3. I. Tsoukalas, C. Makropoulos, and S. Mihas, Identification of potential sewer mining locations: A Monte-Carlo based approach, Water Science and Technology, 76 (12), 3351–3357, doi:10.2166/wst.2017.487, 2017.
4. C. Makropoulos, E. Rozos, I. Tsoukalas, A. Plevri, G. Karakatsanis, L. Karagiannidis, E. Makri, C. Lioumis, K. Noutsopoulos, D. Mamais, K. Ripis, and T. Lytras, Sewer-mining: A water reuse option supporting circular economy, public service provision and entrepreneurship, Journal of Environmental Management, 216, 285–298, doi:10.1016/j.jenvman.2017.07.026, 2018.

Our works that reference this work:

1. C. Makropoulos, and D. Savic, Urban hydroinformatics: past, present and future, Water, 11 (10), 1959, doi:10.3390/w11101959, 2019.

Tagged under: Students' works, Urban water