Novel Evaluation Framework for Pollution-Carbon Coordination in Wastewater Treatment Systems Integrating Influent Temporal Autocorrelation

Wastewater treatment systems face increasing pressure to balance pollution reduction with carbon control under climate-driven environmental variability. This study proposes a novel evaluation framework that integrates temporal autocorrelation analysis with pollution–carbon coordination assessment to address critical methodological gaps in current static evaluation approaches. The framework comprises a coupling coordination degree (CCD) index combining gray water footprint reduction efficiency and carbon emission intensity, systematic incorporation of the autocorrelation coefficient to characterize persistent influent fluctuation patterns, and an integrated prediction methodology for stability evaluation. The framework was validated through a 1,461-day study across four full-scale wastewater treatment plants encompassing Oxidation Ditch (OD), Anaerobic/Anoxic/Oxic (A2/O), A2/O with Membrane Bioreactor (A2/O-MBR), and Cyclic Activated Sludge System (CASS). Advanced configurations achieved superior coordination, with CASS and A2/O-MBR showing mean CCD values of 0.645 and 0.641 versus 0.572 and 0.591 for OD and A2/O processes. CASS maintained 94% of values within the primary coordination range, while A2/O-MBR achieved 85% combined presence in primary and intermediate levels. Temporal autocorrelation emerged as the primary stability determinant, with optimal performance at ACC values between −0.1 and 0.2. Deviations to ACC = ±0.8 increased the coefficient of variation by 34–68% and reduced high-coordination days by up to 27%. Sensitivity rankings positioned A2/O-MBR as the highest, followed by OD, CASS, and A2/O. The framework offers transferable methodological tools for technology selection and optimization, supporting evidence-based design of resilient wastewater infrastructure that explicitly accounts for temporal dynamics in pollution–carbon management strategies.