PRAISE-HK: A personalized real-time air quality informatics system for citizen participation in exposure and health risk management. (March 2020) - Che, Wenwei; Frey, H. Christopher; Fung, Jimmy C.H.; Ning, Zhi; Qu, Huamin; Lo, Hong Kam; Chen, Lei; Wong, Tze-Wai; Wong, Michelle K.M.; Lee, Ophelia C.W.; Carruthers, David; Cheung, Freeman; et al.
Highlights: Developed a personalized real-time air quality forecasting system. Integrated air quality modelling systems, big data and sensor technologies. High agreement of predicted and observed air quality. Interactive mobile application to engage citizens in exposure management. Abstract: Exposure to air pollutants causes a range of adverse health effects. These harmful effects occur whenever and wherever people come into direct contact with air pollution. Therefore, individual actions that reduce the frequency, duration, and severity of personal contact with air pollution can reduce health risks. We developed a system that empowers the public with personalized information on air quality and exposure health risk. This system, the Personalised Real-Time Air Quality Informatics System for Exposure – Hong Kong (PRAISE-HK, http://praise.ust.hk/ ), is embodied in an interactive mobile application. PRAISE-HK is based on real-time data on emissions, high resolution urban morphology, meteorology, physical and chemical processes affecting pollutant transport and transformations, extensive measurements of air pollution concentrations in typical locations such as homes, schools, offices, and transportation, and big data integration of sensor monitoring to accurately estimate current and short-term forecasted street-level air quality. The street-level air quality simulation has been validated against reference monitoring data. Ongoing and planned future enhancements to PRAISE-HK include prediction of personal exposure and health response. PRAISE-HK is an example of the use of collective intelligence in a smart city to engage citizens in learning about and managing their own exposure to air pollution.