Demographic growth in developing countries has increased domestic wastewater generation, posing environmental and health risks due to nitrogen and phosphorus accumulation, the main contributors to eutrophication. This study explores microalgae–bacteria consortia for nutrient removal, using Chlorella sp. for its high pollutant assimilation efficiency and biomass production. A lab-scale experiment was designed using response surface methodology to optimize key variables, revealing that lighting and the culture medium significantly influenced biomass production and nutrient removal, with lighting having the strongest statistical impact (p = 0.0002). The optimal conditions (18 μmolm⁻² s⁻¹ light, municipal wastewater) achieved nitrogen and phosphorus removal efficiencies of 87.16% and 94.43%, respectively. A mathematical model was developed with two independent systems: (1) the first describes biomass generation via photosynthesis, considering CO₂ as a limiting substrate, while (2) the second models nitrogen and phosphorus consumption, assuming nitrogen as limiting substrate and introducing an intermediate (I) that couples phosphorus and nitrogen removal. This coupling is regulated by factor k, which represents a percentage of the total consortium consumption rate. Model predictions showed high accuracy for biomass (SE = 0.07186) and phosphorus (SE = 0.63065), but nitrogen exhibited greater deviation (SE = 3.40285). These findings highlight the system’s potential as a sustainable and cost-effective wastewater treatment alternative.

This paper presents sensitivity and resilience analyses for a trigeneration system designed for a hospital. The following information is utilized to formulate an integer linear programming model: (1) energy service demands of the hospital, (2) technical and economical characteristics of the potential technologies for installation, (3) prices of the available utilities interchanged, and (4) financial parameters of the project. The solution of the model, minimizing the annual total cost, provides the optimal configuration of the system (technologies installed and number of pieces of equipment) and the optimal operation mode (operational load of equipment, interchange of utilities with the environment, convenience of wasting cogenerated heat, etc.) at each temporal interval defining the demand. The broad range of technical, economic, and institutional uncertainties throughout the life cycle of energy supply systems for buildings makes it necessary to delve more deeply into the fundamental properties of resilient systems: feasibility, flexibility and robustness. The resilience of the obtained solution is tested by varying, within reasonable limits, selected parameters: energy demand, amortization and maintenance factor, natural gas price, self‐consumption of electricity, and time‐of‐delivery feed‐in tariffs.