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严重的地区。儿童和学生运动员特别容易受到空气污染水平升高的影响，因为他们的肺部尚未完全发育，呼吸频率更快。目前的空气质量预测和测量未能保护他们免受灰尘和野火烟雾等关键空气质量危害。犹他州是一个典型的例子，那里的空气质量受到野火烟雾和风吹灰尘的严重挑战。这些事件的地理范围和严重程度难以评估，因为国营监测站很少，许多农村县没有空气质量测量手段。犹他州的州和媒体机构只提供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，仅为24小时，并且仅限于臭氧和细颗粒物（即，2.5微米级分）。它们不包括灰尘，也不考虑污染的空间变异性。犹他州目前的预测框架不是自动化的，需要专家工作人员的输入。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，并且没有考虑到海拔变化和粗糙地形造成的微气候或大气变化。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。它使社区，特别是学生体育教练，创造邻里规模，可操作的空气质量信息，以帮助减少暴露于空气污染物的危害，特别是对儿童和青少年参加体育运动。除了对保护公众健康产生更广泛的影响外，该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传播方面取得进展。CIVIC创新挑战赛是与能源部、国土安全部和国家科学基金会合作开展的。这个公民创新挑战项目将与社区规模的利益相关者共同开发可操作的空气质量信息，以帮助减少暴露于空气污染物危害，包括野火烟雾和灰尘，特别是对儿童。它将建立在项目团队现有的空气质量传感和预测基础设施以及它为收集和评估必要的测量而建立的强大的公民伙伴关系的基础上。预测工具、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。该项目将扩大犹他州大学现有的空气质量传感基础设施，增加新的灰尘传感能力，并扩大其创新的空气质量传感网络的地理覆盖范围。然后，这些数据与现有的气象、灰尘输送、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。这将通过来自犹他州大学的大学研究人员、学校系统决策者（例如，preK-12管理员和运动训练员），和管理机构（犹他州空气质量部门，卫生部和犹他州高中活动协会）。这种团队方法以及数据和创建具有易于访问界面的数据可视化工具的创新组合将导致高分辨率（即，4公里的水平分辨率和传感器的每小时读数），自动化系统，产生空气污染危害的数值预报，特别是与逆温、野火烟雾和灰尘有关的数值预报。该系统将实施一个新的、具有成本效益的、空气质量传感器，用于监测和预测严重的灰尘水平和其他颗粒气载物质，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知识价值和更广泛的评估被认为值得支持影响审查标准。

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.