CIVIC - FA Track A: Pilot - Community Resilience through Engaging, Actionable, Timely, High - REsolution Air Quality Information (CREATE - AQI)

美国有超过1.37亿人生活在室外空气污染水平不健康的地区。儿童和学生运动员特别容易受到空气污染水平上升的影响，因为他们的肺部没有完全发育，而且他们的呼吸频率更快。目前的空气质量预报和测量未能保护他们免受严重的空气质量危害，如粉尘和野火烟雾。犹他州是一个受野火、烟雾和风尘影响而面临严重空气质量挑战的地方的典型例子。这些事件的地理范围和严重程度很难评估，因为国营监测站稀少，许多农村县没有空气质量测量手段。犹他州的州和媒体只提供了29个县中12个县的空气质量预报，这些预报的空间分辨率低，只有24小时的预报，而且仅限于臭氧和细颗粒物(即2.5微米级的颗粒物)。它们不包括灰尘，也不能解释污染的空间变异性。犹他州目前的预测框架不是自动化的，需要专家工作人员提供意见。此外，由于犹他州地形复杂，联邦机构提供的当地空气质量预报和空气质量地图可能非常不准确，因为它们是为整个美国大陆设计的，没有考虑到海拔变化和粗糙地形造成的小气候或大气变幻莫测。该项目通过创新的建模和数据收集机制和方法提供高分辨率的空气质量数据。它动员社区，特别是学生体育教练，创建社区规模的、可操作的空气质量信息，以帮助减少接触空气污染物危害，特别是参与体育运动的儿童和青年。除了保护公众健康的更广泛影响外，这项研究还将在自动空气质量预报、社区规模的空气质量传感网络和科学交流方面取得进展。公民创新挑战是与能源部、国土安全部和国家科学基金会的合作。这一公民创新挑战项目将与社区规模的利益攸关方共同开发可操作的空气质量信息，以帮助减少暴露在空气污染物危害中，包括野火、烟雾和粉尘，特别是对儿童来说。它将建立在项目组现有的空气质量监测和预报基础设施以及为收集和评估必要的测量而发展的强有力的民间伙伴关系的基础上。预报工具、有效的信息传递策略和质量指标将帮助社区保护犹他州的儿童、运动员和公众免受空气质量危害。该项目将通过增加新的粉尘传感能力，并扩大其创新空气质量传感网络的地理覆盖范围，来扩展犹他大学现有的空气质量传感基础设施。然后将这些数据与现有的气象、沙尘输送、野火烟雾输送、空气质量预报模型相结合，生成自动化的、高空间分辨率的空气质量预报。这将通过来自犹他大学的大学研究人员、学校系统决策者(例如，K-12学龄前管理人员和运动训练员)和管理机构(犹他州空气质量司、卫生部和犹他州高中活动协会)的参与来完成。这一团队方法和数据与数据可视化工具的创新组合以及易于访问的界面将产生高分辨率(即4公里的水平分辨率和传感器每小时的读数)，这是一个自动化系统，可以产生空气污染危害的数值预报，特别是与逆温、野火烟雾和粉尘有关的危害。该系统将运行一种新的、经济高效的空气质量传感器，并将其整合到国家空气质量系统中，以监测和预测严重的粉尘水平和其他空气中的颗粒物，这些物质可以通过交互式仪表板可视化，以了解何时存在危险水平。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Over 137 million people in the US live in areas with unhealthy levels of outdoor air pollution. Children and student athletes are particularly vulnerable to elevated air pollution levels because their lungs are not fully developed, and they have more rapid breathing rates. Current air quality forecasts and measurements fail to protect them from critical air quality hazards, like dust and wildfire smoke. Utah is a prime example of a place with serious air quality challenges driven by wildfire smoke and wind-blown dust. The geographic extent and severity of these events is difficult to assess because State-run monitoring stations are sparse and many rural counties have no means of air quality measurement. Utah’s state and media outlets only provide air-quality forecasts for 12 of 29 counties and these have low spatial resolution, are only for a 24-hour period, and are limited to ozone and fine particulate matter (i.e., 2.5 micron size fraction). They do not include dust nor do they account for the spatial variability of the pollution. Utah’s current forecasting framework is not automated and requires input from expert staff. Furthermore, due to Utah’s complex terrain, local air-quality forecasts and air quality maps provided by federal agencies can be highly inaccurate because they are designed for the entire continental U.S. and do not account for microclimates or atmospheric vagaries caused by elevation changes and rough terrane. This project provides high resolution air quality data through innovative modeling and data gathering mechanisms and approaches. It engages the community, in particular student athletic coaches, to create neighborhood-scale, actionable air quality information to help reduce exposure to air pollutant hazards, particularly for children and youth participating in athletics. In addition to its broader impact of protecting public health, the research will make advances in automated air-quality forecasting, community-scale air quality sensing networks, and science communication.The CIVIC Innovation Challenge is a collaboration with Department of Energy, Department of Homeland Security, and the National Science Foundation. This Civic Innovation Challenge project will co-develop with stakeholders at the neighborhood-scale, actionable air quality information to help reduce exposure to air pollutant hazards including wildfire smoke and dust, particularly for children. It will build off the project team's existing air-quality sensing and forecasting infrastructure as well as strong civic partnerships it has developed to collect and evaluate the necessary measurements. The forecasting tools, effective message-delivery strategies, and quality metrics will help the community protect children, athletes, and the public in Utah from air-quality hazards. The project will expand the University of Utah’s existing air quality sensing infrastructure by adding new sensing capabilities for dust and extending the geographic coverage of its innovative air quality sensing network. These data are then integrated with existing meteorological, dust transport, wildfire smoke transport, air-quality forecasting models to generate automated, high, spatial resolution, air quality forecasts. This will be done through the involvement of university researchers from the University of Utah, school system decision makers (e.g., preK-12 administrators and athletic trainers), and governing bodies (the Utah Division of Air Quality, Health Department and Utah High School Activities Association). This team approach and the innovative combination of data and creation of data visualization tools with an easily accessible interface will result in a high-resolution (i.e., 4-km horizontal resolution and hourly readings from sensors), automated system that produces numerical forecasts of air pollution hazards, in particular those related to inversions, wildfire smoke, and dust. The system will operationalize and integrate into the State air quality system a new, cost-effective, air quality sensor to monitor and predict serious dust levels and other particulate airborne matter that can be visualized through an interactive dashboard to understand when dangerous levels are present.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.