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

在城市地区，交通是主要的空气污染源，在加拿大和其他地方，与交通有关的空气污染与各种形式的癌症、心血管和呼吸系统健康影响有关。城市空气污染表现出巨大的季节性和空间变异性，这对于以下方面至关重要：a)健康影响研究；b)变革性交通系统（自动驾驶汽车、电动汽车、叫车服务）对城市空气质量影响的研究；以及c)针对弱势群体的暴露管理工具的开发。空气污染监测问题及其对大城市地区暴露面发展的价值是一个活跃的研究领域。迄今为止，很少有工作成功地证明了利用实时监测数据生成空气质量空间预测的能力，而且也是实时的。这些努力往往受到所用监测设备不足的限制。******虽然最近低成本空气污染传感器的发展开辟了收集密集空气污染数据的新方法，但大多数传感器在准确捕捉城市空气污染时空变化的能力方面是有限的，这一点很重要。大多数商用气体和颗粒传感器都给研究人员带来了有意义的数据收集方面的重大挑战。事实上，传感器本身的质量与围绕它构建的“智能”和数据处理算法一样重要。******所提出的传感器将克服现有商用传感器的许多限制。这些装置集成了自校准功能，允许用户远程访问各种诊断，确保系统在现场进行可靠的测量。它们还可以承受振动，因此特别适合移动测量，这对于实现高空间覆盖至关重要。如果获得成功，这笔拨款将使我们能够购买15台设备，促进现有传感器尚未可行的一系列研究的发展，并使我的研究小组能够设计和实施独特的空气污染监测活动，旨在以无与伦比的精度开发城市空气质量的时空预测。**

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. **