Tracing wastewater resources: unravelling the circularity of waste using source, destination, and quality analysis

Abstract

Data availability: Data will be made available on request.Supplementary materials are available online at: https://www.sciencedirect.com/science/article/pii/S0043135423013416#sec0037 .Copyright © 2023 The Authors. Current circularity assessment terminology restricts application to wastewater processes due to the focus on technical systems. Waste stream and wastewater discharge circularity definitions lead to paradoxical assessments that generate results of little value for evidence-based decision making. Therefore, a classification approach was developed to measure inflow and outflow circularity of the main wastewater resource flows using the principle of traceability, adopting the attitude that not all waste is created equally. Applying it to a wastewater treatment plant (12,000 m3/d load) showed how upstream agricultural, industrial, and human practices impact downstream treatment, and the effectiveness of resource cycling within the natural environment. Industrial actions increasing fossil carbon concentration (400 m3/d effluent at 1000 mgC/l) reduced inflow and outflow circularity by 16 % and 10.6 % respectively, as secondary and sludge treatment fossil emissions increase significantly. Alternatively, changes to human and agricultural practices (50 % reduction of detergent and synthetic fertiliser usage) improved phosphorus inflow and nitrogen outflow circularity by 5.2 % and 20.1 % respectively. This approach can educate and assign responsibility to water users for developing robust circular economy policy, shifting the pattern from promoting circularity to discouraging linear actions, overcoming the shared economic and environmental burden of linear water use.This research was supported by the Horizon 2020 research and innovation programme DEEP PURPLE. The H2020 DEEP PURPLE project has received funding from the Bio-based Industries Joint Undertaking (JU) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 837998. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio-based Industries Consortium