Abstract The use of low-cost air pollution sensors mounted on drones is an exciting new approach to conduct affordable and highly resolved air quality measurements. However, the air flow around a drone consists of complex, unsteady turbulent structures which interact directly with ambient particulate matter and gases. These interactions influence the transport of fine particulate matter (e.g. PM2.5) and, subsequently, its measurement using on-board PM sensors. In this work, we aim to quantify this effect by conducting wind tunnel and open-air experiments using a quadrotor drone and an array of low-cost sensors and research grade instruments. Sensors and instruments were placed around the drone to assess the effect of mixing, dilution, and particle segregation in the wake generated by the drone. Our results indicate little impact on the shape of the particle size distribution but significant differences (p 0.05) in PM2.5 concentration ranging from -70% to greater than 400% when comparing measurements before and after the drone is turned on. These effects varied greatly with sensor location and across experiments. In the wind tunnel, the sensor least affected was located far upstream from the drone with concentration differences less than 7%. The sensor far downstream from the drone as well as one of the sensors to the side of the drone also showed relatively small concentration differences (

中文翻译：

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无人机测量颗粒物的有效性

摘要 使用安装在无人机上的低成本空气污染传感器是一种令人兴奋的新方法，可以进行价格合理且分辨率高的空气质量测量。然而，无人机周围的气流由复杂的、不稳定的湍流结构组成，这些结构直接与周围的颗粒物和气体相互作用。这些相互作用会影响细颗粒物（例如 PM2.5）的传输，进而影响其使用机载 PM 传感器的测量。在这项工作中，我们的目标是通过使用四旋翼无人机和一系列低成本传感器和研究级仪器进行风洞和露天实验来量化这种影响。传感器和仪器被放置在无人机周围，以评估无人机产生的尾流中的混合、稀释和粒子分离的影响。我们的结果表明，在比较无人机启动前后的测量值时，对粒径分布的形状影响很小，但 PM2.5 浓度的显着差异（p = 0.05）从 -70% 到大于 400%。这些影响因传感器位置和实验而异。在风洞中，受影响最小的传感器位于距离无人机较远的上游，浓度差异小于 7%。远离无人机下游的传感器以及无人机侧面的一个传感器也显示出相对较小的浓度差异（这些影响因传感器位置和实验而异。在风洞中，受影响最小的传感器位于距离无人机较远的上游，浓度差异小于 7%。远离无人机下游的传感器以及无人机侧面的一个传感器也显示出相对较小的浓度差异（这些影响因传感器位置和实验而异。在风洞中，受影响最小的传感器位于距离无人机较远的上游，浓度差异小于 7%。远离无人机下游的传感器以及无人机侧面的一个传感器也显示出相对较小的浓度差异（