EAGER: Incorporating Citizen Science into Real-Time Sensor-Based Estimates of Traffic-Related Air Pollution Exposure

1645226随着传感器技术的快速发展，它们变得更容易被公民科学家使用；然而，如果使用这些传感器时不完全了解它们的功能和限制，可能会导致数据因操作偏差而不可靠。这项工作的主要目标是部署低成本的空气质量传感器，提供高质量的数据，从而更好地估计个人接触空气污染物的情况。具体地说，这项工作将集中在与交通相关的空气污染(TRAP)，即一氧化碳、臭氧(O3)、二氧化氮(NO2)和颗粒物(PM)。该项目将通过与一个由俄亥俄州哥伦布市附近的当地高中生组成的公民科学家团队合作进行。公民科学家和研究团队将共同为教师或其他学生开发培训模块，以便在希利亚德市学区接触到更广泛的受众。人们认识到，目前针对公民科学使用的技术存在局限性，即公民科学家可以利用低成本的空气质量传感器来提供他们生活、工作和娱乐的微环境中可靠的空气质量数据。最初，这将需要私人投资机构的谨慎指导，但在未来，随着培训材料的编制，将需要有限的监督。PIS制定了一项具有以下目标的项目计划：1.聘请和招募公民科学家来制造和部署支持Wi-Fi的低成本空气质量传感器网络；2.使用传感器网络监测俄亥俄州富兰克林县希利亚德市学区的环境空气质量。3.开发和部署云计算解决方案，以此传感器网络为基础提供公共可用的、接近实时的空气质量数据。4.开展外展活动，让高中生了解他们居住、玩耍和上学所在社区的当地空气质量。整个研究计划被组织成一系列任务。任务1是由公民科学家制造空气质量监测仪，任务2是使用这些监测仪作为传感器网络进行室外空气质量测量，任务3是对收集的数据进行解释和可视化。这项工作将有助于低成本空气污染传感器的开发、改进和实际应用，重点是由民间科学家部署本地传感器网络。通过提供云计算解决方案来处理传感器网络收集的数据，PI可以解决偏差和离群值，从而缓解了与数据可靠性、有效性和可信性相关的一些担忧。这个项目将在促进教学、培训和学习的同时造福社会。部署的空气质量监测网络将提供俄亥俄州希利亚德市学区关键微环境中个人暴露于空气污染的估计，从而为地区居民预防或管理急性哮喘恶化提供更好的做法。该奖项由CSISE大数据中心(BDHubs)计划共同资助。

1645226MayAs sensor technologies rapidly evolve, they become more accessible for citizen scientist use; however, use of these sensors with incomplete understanding of their capabilities and limitations can result in data that may be unreliable due to operational biases. The key aim of this work is to deploy low-cost air quality sensors that provide high-quality data, resulting in better estimates of personal exposure to air pollutants. Specifically, this work will focus on traffic-related air pollution (TRAP), namely carbon monoxide, ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM). The project will be conducted through collaboration with a team of citizen scientists comprised of local high school students near Columbus, OH. Jointly, the citizen scientists and research team will develop training modules for teachers or other students in order to reach a broader audience at Hilliard City School District.It is recognized that there are limitations of current technologies targeted for use in citizen science, the PIs' hypothesize that low-cost air quality sensors can be utilized by citizen scientists to provide reliable air quality data within micro-environments where they live, work and play. Initially, this will require careful guidance from the PIs, but in the future, limited oversight will be needed as training materials are developed. The PIs have developed a project plan with the following objectives: 1. Engage and recruit citizen scientists to fabricate and deploy a Wi-Fi-enabled, low-cost air quality sensor network, 2. Monitor ambient air quality with the sensor network in the Hilliard City School District in Franklin County, OH. 3. Develop and deploy a cloud-computing solution to provide publically-available, near-real-time air quality data based on this sensor network. 4. Develop outreach activities to engage high school students about local air quality within their neighborhoods where they live, play and go to school. The overall research plan is organized into a series of tasks. Task 1 is the fabrication of the air quality monitors by the citizen scientists, Task 2 is the use of these monitors to conduct outdoor air quality measurements as a sensor network, and, Task 3 is the interpretation and visualization of the data collected. This work will contribute to the development, refinement, and practical application of low-cost air pollution sensors with an emphasis on deployment of local sensor networks by citizen scientists. By providing a cloud-computing solution to process the data collected by the sensor network, the PI can account for biases and outliers, thus mitigating some of the concerns related to data reliability, validity, and trustworthiness. This project will benefit society while promoting teaching, training, and learning. The deployed network of air quality monitors will provided estimates of personal exposure to air pollution within key micro-environments in the Hilliard City School District in Hilliard, OH, thus enabling better practices for prevention or management of acute asthma exacerbation for district residents. This award received co-funding from CISE Directorate Big Data Hubs (BDHubs) Program.