SchoolAIR: A Citizen Science IoT Framework Using Low-Cost Sensing for Indoor Air Quality Management.

Indoor air quality (IAQ) problems in school environments are very common and have significant impacts on students' performance, development and health. Indoor air conditions depend on the adopted ventilation practices, which in Mediterranean countries are essentially based on natural ventilation controlled through manual window opening. Citizen science projects directed to school communities are effective strategies to promote awareness and knowledge acquirement on IAQ and adequate ventilation management. Our multidisciplinary research team has developed a framework-SchoolAIR-based on low-cost sensors and a scalable IoT system architecture to support the improvement of IAQ in schools. The SchoolAIR framework is based on do-it-yourself sensors that continuously monitor air temperature, relative humidity, concentrations of carbon dioxide and particulate matter in school environments. The framework was tested in the classrooms of University Fernando Pessoa, and its deployment and proof of concept took place in a high school in the north of Portugal. The results obtained reveal that CO2 concentrations frequently exceed reference values during classes, and that higher concentrations of particulate matter in the outdoor air affect IAQ. These results highlight the importance of real-time monitoring of IAQ and outdoor air pollution levels to support decision-making in ventilation management and assure adequate IAQ. The proposed approach encourages the transfer of scientific knowledge from universities to society in a dynamic and active process of social responsibility based on a citizen science approach, promoting scientific literacy of the younger generation and enhancing healthier, resilient and sustainable indoor environments.

Considerations on the monitoring of water quality in urban streams: a case study in Portugal.

Monitoring water quality in urban stream is of utmost importance for water resources managers, who are pressured to optimize monitoring schemes in order to reduce costs. The present study aims to use the results of a 2-year-long water quality monitoring program of an urban stream in Portugal to identify improvement opportunities. The urban stream under study was subjected to wastewater treatment plants effluent discharges, leachates from a major sealed landfill, low-class housing effluents, and nonpoint sources of pollution. Contributing watersheds are mostly artificial surfaces and agricultural land, which irrigate directly from the river. River water quality was evaluated on 11 sampling locations for 24 months from October 2013 to September 2015. The present paper describes statistical analysis of the results obtained for 12 physicochemical parameters in order to optimize the monitoring scheme. Cluster analysis detected a seasonal variation in the water quality and a spatial pattern based on the major point sources of pollution. A factor analysis showed that the parameters that mostly contribute to water quality assessment in this urban river are alkalinity, ammonia, electrical conductivity, pH, temperature, and dissolved oxygen. Results suggest that the monitoring efforts-and associated costs-may be reduced by decreasing monitoring frequency, sampling points, and monitored parameters. The statistical analysis described in this study may be replicated in other water quality monitoring programs, providing useful and important information for the systematic and iterative assessment of the adequacy of water quality sampling programs towards a sustainable management of water quality surveillance.