Towards operational net-zero pathways in industrial wastewater treatment systems using digital decision support tools

Area of Science:

• Environmental Engineering
• Climate Science
• Industrial Ecology

Background:

• Effective green transition strategies necessitate accurate greenhouse gas (GHG) emissions quantification and evaluation of operational regimes.
• Water treatment systems (WTS) are significant contributors to industrial emissions, requiring targeted mitigation approaches.
• Digital decision support tools (DSTs) can aid in assessing and achieving net-zero targets within complex industrial operations.

Purpose of the Study:

• To develop and validate a digital decision support tool (DST) for assessing and achieving net-zero targets in industrial water treatment systems (WTS).
• To integrate mathematical models for simulating WTS behavior, operational costs, and comprehensive GHG emissions (Scope 1, 2, 3, and avoided emissions).
• To analyze the impact of various mitigation scenarios on GHG emissions and operational performance.

Main Methods:

• Development of an integrated DST combining mathematical models to simulate WTS performance (effluent quality, energy, costs).
• Construction of a GHG emissions module to quantify direct emissions (DE), energy-related emissions (ERE), upstream/downstream emissions (UDE), and avoided emissions (AE), including biogenic CO2.
• Simulation of four distinct mitigation scenarios (S1-S7) focusing on carbon management, N2O reduction, and biogas upgrading.

Main Results:

• The DST accurately reproduced WTS mass balances (9.3% deviation), dynamic performance (11.3% deviation), energy balances (3.8-5.0% deviation), and operational expenditures (3.9-4.3% deviation).
• Operational emissions averaged 5.6 kg CO2-eq/m3, with DE (39%), ERE (9%), and UDE (52%) as major contributors. N2O dominated DE, and sludge treatment drove UDE.
• Avoided emissions from fertilizer and natural gas substitution counterbalanced operational emissions, achieving a net-zero performance of -0.2 kg CO2-eq/m3. Scenarios S1, S6, and S7 demonstrated net-negative performance (-2.1 kg CO2-eq/m3).

Conclusions:

• The integrated DST provides a robust framework for evidence-based decision-making in optimizing resource use and minimizing emissions in WTS.
• Certain mitigation strategies (S1, S6, S7) can achieve net-negative operational GHG performance by maximizing avoided emissions.
• Alternative strategies (S2-S5) may fail to meet net-zero targets due to increased N2O emissions or higher operational demands, highlighting the importance of tailored mitigation planning.