Assessment and optimization of wastewater treatment plant in terms of effluent quality, energy footprint, and greenhouse gas emissions: An integrated modeling approach.

Wastewater treatment plants (WWTPs) can benefit from utilizing digital technologies to reduce greenhouse gas (GHG) emissions and to comply with effluent quality standards. In this study, the GHG emissions and electricity consumption of a WWTP were evaluated via computer simulation by varying the dissolved oxygen (DO), mixed liquor recirculation (MLR), and return activated sludge (RAS) parameters. Three different measures, namely, effluent water quality, GHG emissions, and energy consumption, were combined as water-energy-carbon coupling index (WECCI) to compare the effects of the parameters on WWTPs, and the optimal operating condition was determined. The initial conditions of the A2O process were set to 4.0 mg/L of DO, 100 % MLR, and 90.7 % RAS. Eighty scenarios with various DO, MLR, and RAS were simulated under steady-state condition to optimize the biological treatment process. The optimal operating conditions were found to be 1.5 mg/L of DO, 190 % MLR, and 90.9 % RAS, which had the highest WECCI of 2.40 when compared to the WECCI of the initial condition (1.07). This optimal condition simultaneously reduced GHG emissions by 1348 kg CO2-eq/d and energy consumption by 11.64 MWh/d. This implies that controlling DO, MLR, and RAS through sensors, valves, and pumps offers a promising approach to operating WWTPs with reduced electricity consumption and GHG emissions while attaining effluent quality standards. Additionally, the nitrous oxide stripping rate exhibited linear relationships with the effluent total ammonia and nitrite concentrations in the aerobic reactor, suggesting that monitoring dissolved nitrogen compounds in the effluent and reactor could be a viable strategy to control MLR and DO in the biological reactor. The digital-based assessment and optimization tools developed in this study are expected to hold promise for application in broader environmental management efforts.

1H-NMR-based metabolomic studies of bisphenol A in zebrafish (Danio rerio).

Proton nuclear magnetic resonance (1H-NMR) spectroscopy was used to study the response of zebrafish (Danio rerio) to increasing concentrations of bisphenol A (4,4'-(propane-2,2-diyl)diphenol, BPA). Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to detect aberrant metabolomic profiles after 72 h of BPA exposure at all levels tested (0.01, 0.1, and 1.0 mg/L). The OPLS-DA score plots showed that BPA exposure caused significant alterations in the metabolome. The metabolomic changes in response to BPA exposure generally exhibited nonlinear patterns, with the exception of reduced levels of several metabolites, including glutamine, inosine, lactate, and succinate. As the level of BPA exposure increased, individual metabolite patterns indicated that the zebrafish metabolome was subjected to severe oxidative stress. Interestingly, ATP levels increased significantly at all levels of BPA exposure. In the present study, we demonstrated the applicability of 1H-NMR-based metabolomics to identify the discrete nature of metabolic changes.