Evolving wastewater infrastructure paradigm to enhance harmony with nature

Abstract

Restoring and improving harmony between human activities and nature are essential to human well-being and survival. The role of wastewater infrastructure is evolving toward resource recovery to address this challenge. Yet, existing design approaches for wastewater systems focus merely on technological aspects of these systems. If system design could take advantage of natural ecological processes, it could ensure infrastructure development within ecological constraints and maximize other benefits. To test this hypothesis, we illustrate a data-driven, systems-level approach that couples natural ecosystems and the services they deliver to explore how sustainability principles could be embedded into the life phases of wastewater systems. We show that our design could produce outcomes vastly superior to those of conventional paradigms that focus on technologies alone, by enabling high-level recovery of both energy and materials and providing substantial benefits to offset a host of unintended environmental effects. This integrative study advances our understanding and suggests approaches for regaining a balance between satisfying human demands and maintaining ecosystems.

Fig. 1. Overview of inputs, internal flows, and outputs of the REPURE approach.

Most of the influent carbon substrates (C) are concentrated in the carbon recovery system (CRS), whereas the resulting C-rich biomass is fermented partly to acetic acid (HAc)–dominant short-chain fatty acids (SCFAs) in the subsequent carbon conversion system (CCS). The HAc-rich liquid serves as a promising carbon source in the partial treatment system (PTS) for nutrient removal. The resulting sludge from CCS and PTS is transformed to various products in the resources harvesting system (RHS). Most of the sludge C is converted to CH₄, whereas the remainder is used for polyhydroxyalkanoate (PHA) synthesis. The wastewater N is converted to N₂O, which is used for combustion with CH₄ for power generation. The sludge P can be recovered as struvite.

Fig. 2. Schematic of a tailored process configuration for the REPURE approach.

This configuration is constructed by three interlinked technological components (SRS, PTS, and RHS) to enable smooth operation and maintenance.

Fig. 3. Long-term performance of the REPURE process configuration.

Dynamic profiles of effluent COD and TP (A), effluent ammonia and TN (B), emitted nitrous oxide and methane (C), and formations of struvite and PHA (D) in the exemplified REPURE configuration. The small box plots in each chart depict the statistical information of the dynamic profiles, the central lines represent median values, the boxes represent the 25th to 75th percentiles, and the bars depict the 5th to 95th percentiles of the distributions resulting from the 600-day simulation.

Fig. 4. Sankey diagram tracing the intersystemic flows of C, N, and P from influent wastewater (from REPURE processing to the delivery of recovered products).

The linewidth is proportional to the mass flux. The average values of the 600-day simulations were used to prepare this figure.

Fig. 5. Energy balance and distribution in the REPURE process configuration.

The left gray area in the chart indicates the energy required for system maintenance, whereas the right white area presents the energy produced from methane combustion and biosolid incineration. The black box presents the net energy gain relative to the system boundary considered, and the average values of the modeling results are shown.

Fig. 6. Net change in and processes contributing to 12 midpoint LCA effects, expressed per cubic meter of wastewater processed over 50 years of operation of the REPURE configuration.

A negative value represents an environmental benefit, whereas positive values indicate an increase in the environmental burden. The relative size, or the apparent absence, of each color reflects the contribution of the process to each effect. The error bars present the best and worst cases of the pathway analyzed. The green or red text indicates statistically the net contribution of the system to each effect resulting from more than 100,000 Monte Carlo simulation runs, and the green means a net benefit for the environment.