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Abstract:With rapid urbanization and infrastructure investment, wastewater treatment plants (WWTPs) in Chinese cities are putting increased pressure on energy consumption and exacerbating greenhouse gas (GHG) emissions. A carbon footprint is provided as a tool to quantify the life cycle GHG emissions and identify opportunities to reduce climate change impacts. This study examined three mainstream wastewater treatment technologies: Anaerobic-Anoxic-Oxic (A-A-O), Sequencing Batch Reactor (SBR) and Oxygen Ditch, considering four different sludge treatment alternatives for small-to-medium-sized WWTPs. Following the life cycle approach, process design data and emission factors were used by the model to calculate the carbon footprint. Results found that direct emissions of CO2 and N2O, and indirect emissions of electricity use, are significant contributors to the carbon footprint. Although sludge anaerobic digestion and biogas recovery could significantly OPEN ACCESSWater 2015, 7 919 contribute to emission reduction, it was less beneficial for Oxygen Ditch than the other two treatment technologies due to its low sludge production. The influence of choosing "high risk" or "low risk" N2O emission factors on the carbon footprint was also investigated in this study. Oxygen Ditch was assessed as "low risk" of N2O emissions while SBR was "high risk". The carbon footprint of A-A-O with sludge anaerobic digestion and energy recovery was more resilient to changes of N2O emission factors and control of N2O emissions, though process design parameters (i.e., effluent total nitrogen (TN) concentration, mixed-liquor recycle (MLR) rates and solids retention time (SRT)) and operation conditions (i.e., nitrite concentration) are critical for reducing carbon footprint of SBR. Analyses of carbon footprints suggested that aerobic treatment of sludge not only favors the generation of large amounts of CO2, but also the emissions of N2O, so the rationale of reducing aerobic treatment and maximizing anaerobic treatment applies to both wastewater and sludge treatment for reducing the carbon footprint, i.e., the annamox process for wastewater nutrient removal and the anaerobic digestion for sludge treatment.

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This study investigates the parametric approach for a type of descriptor quasi-linear systems by utilising dynamic compensator and multi-objective optimisation. Based on the solutions of generalised Sylvester matrix equation, the generally parameterised expressions of dynamic compensator and the left and right eigenvector matrices are both established, meanwhile, a group of arbitrary parameters are obtained. With the parametric approach, the closed-loop system can be transformed into a linear time-invariant one with an expected eigenstructure by using a group of canonical matrix pairs. Simultaneously, it also presents a novel technique to design multi-objective optimisation for descriptor quasi-linear systems.Multiple performance indexes such as low sensitivity, disturbance attenuation, robustness degree, and low gains are formulated by arbitrary parameters. Based on the above indexes, robustness criteria and low gain criteria can be expressed by a synthetic objective function which includes each performance index weighted. By utilising the degrees of freedom in arbitrary parameters, a dynamic compensator can be obtained by solving a multi-objective optimisation problem. Finally, two examples are proposed to prove that the parametric approach is effective.

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