Air quality sensors for mobile air monitoring and real-time air pollution mapping

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In urban areas, traffic is the primary air pollution source and traffic-related air pollution (TRAP) has been linked with various forms of cancer, cardiovascular, and respiratory health effects, both in Canada and elsewhere. Urban air pollution exhibits substantial seasonal and spatial variability that is important to capture in a) health effects studies, b) studies of the impacts of transformative transportation systems (automated vehicles, electric vehicles, ride hailing services) on urban air quality, and c) the development of exposure management tools geared at vulnerable individuals. The question of air pollution monitoring and its value for the development of exposure surfaces at the level of large urban areas is an active field of research. To date, very few efforts have successfully demonstrated the ability to use real-time monitoring data for the generation of spatial predictions of air quality, also in real-time. These efforts are often limited by the inadequacy of the monitoring equipment used. ******While it is important to acknowledge that the recent development of low-cost air pollution sensors has opened up new ways of collecting dense air pollution data, most sensors are limited in terms of their ability to accurately capture the spatio-temporal variability of urban air pollution. Most commercial gas and particulate sensors have presented researchers with significant challenges for meaningful data collection. In fact, the quality of the sensor itself is as important as the “intelligence” and data processing algorithms built around it.******The proposed sensors will overcome many of the limitations of existing commercial sensors. These units integrate capability for self-calibration and allow the user to access various diagnostics remotely, ensuring reliable measurements are taken while the system is in the field. They can also withstand vibration and are therefore particularly suited for mobile measurements, which are critical for achieving high spatial coverage. If successful, this grant will enable the purchase of 15 units, promoting the development of a range of studies that have not yet been feasible with existing sensors, and allowing my research group to design and implement unique air pollution monitoring campaigns geared towards developing spatio-temporal predictions of urban air quality at unparalleled levels of accuracy. **