RESUMEN
The recent pandemic increased attention to the need for appropriated ventilation and good air quality as efficient measures to achieve safe and healthy indoor air. This work provides a novel methodology for continuously evaluating ventilation in public areas using modern rapid response sensors (RRS). This methodology innovatively assesses the ventilation of a space by combining a quantitative estimation of the real air exchange in the space-obtained from CO2 experimental RRS measurements and the characteristics of and activity in the space-and indoor and outdoor RRS measurements of other pollutants, with healthy recommendations from different organisations. The methodology allows space managers to easily evaluate, in a continuous form, the appropriateness of their ventilation strategy, thanks to modern RRS measurements and direct calculations (implemented here in a web app), even in situations of full activity. The methodology improves on the existing standards, which imply the release of tracer gases and expert intervention, and could also be used to set a control system that measures continuously and adapts the ventilation to changes in indoor occupancy and activity, guaranteeing safe and healthy air in an energy-efficient way. Sample public concurrence spaces with different conditions are used to illustrate the methodology.
RESUMEN
The proposed methodology for optimizing energy efficiency, based on good management of the aeration process through the implementation of an appropriate control strategy, achieved reductions of more than 40% in energy consumption at the San Pedro del Pinatar Wastewater Treatment Plant (WWTP) (Murcia, Spain). Phases I and II of this methodology managed to reduce the oxygen needs of the microorganisms in the biological system, optimize the efficiency of oxygen transfer to the biological reactor and redesign the installation to correct abnormal energy loss situations. In addition, we established the basis for Phase III, which implemented a control strategy to achieve stable values close to the setpoints of the fundamental operating parameters of the aeration process. The control system is based on the measurements recorded by strategically installed sensors and mathematical algorithms based on models, achieving an expert adaptive-predictive system that regulates aeration both in the biological stage by activated sludge and the aeration of the installed ultrafiltration membrane system. The objectives were: (i) to achieve automatic execution of the best management strategy; (ii) to reduce the energy demand; (iii) to improve the operation and stability of the process; (iv) to reduce operating costs; and (v) to contribute to the fulfillment of the sustainable development objectives.