Transit activities are a significant contributor to a person’s daily exposure to pollutants. Currently obtaining accurate information about the personal exposure of a commuter is challenging as existing solutions either have a coarse monitoring resolution that omits subtle variations in pollutant concentrations or are laborious and costly to use. We contribute by systematically analysing the feasibility of using wearable low-cost pollution sensors for capturing the total exposure of commuters. Through extensive experiments carried out in the Helsinki metropolitan region, we demonstrate that low-cost sensors can capture the overall exposure with sufficient accuracy, while at the same time providing insights into variations within transport modalities. We also demonstrate that wearable sensors can capture subtle variations caused by differing routes, passenger density, location within a carriage, and other factors. For example, we demonstrate that location within the vehicle carriage can result in up to $25\%$ increase in daily pollution exposure – a significant difference that existing solutions are unable to capture. Finally, we highlight the practical benefits of low-cost sensors as a pollution monitoring solution by introducing applications that are enabled by low-cost wearable sensors.

交通活动是一个人每天接触污染物的重要因素。目前获取有关通勤者个人暴露的准确信息具有挑战性，因为现有的解决方案要么具有粗略的监测分辨率，忽略了污染物浓度的细微变化，要么使用费力且成本高昂。我们通过系统地分析使用可穿戴低成本污染传感器来捕获通勤者的总暴露量的可行性做出贡献。通过在赫尔辛基大都市区进行的大量实验，我们证明低成本传感器可以足够准确地捕获整体曝光，同时提供对交通方式变化的洞察。我们还证明了可穿戴传感器可以捕获由不同路线引起的细微变化，乘客密度、车厢内的位置和其他因素。例如，我们证明了车厢内的位置可以导致高达$25\%$日常污染暴露增加——现有解决方案无法捕捉到的显着差异。最后，我们通过介绍由低成本可穿戴传感器实现的应用，强调了低成本传感器作为污染监测解决方案的实际优势。