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

规划：CIVIC-PG 轨道 A：试点 - 通过参与、可操作、及时、高分辨率的空气质量信息 (CREATE-AQI) 提高社区复原力

• 批准号: 2228600
• 负责人: Kerry Kelly
• 金额: $ 5万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2228600&HistoricalAwards=false
• 关键词: Planning; CIVIC; PG; Track; Pilot

More than forty percent of all people in the United States — over 137 million people — live in areas with unhealthy levels of air pollution due to particulate matter or ozone. Communities with poor air quality are predominately found in the Western US in underserved areas. The Western US periodically experiences the worst air quality in the nation as a result of winter-time inversions, wildfires, and dust storms. It can be difficult for individuals in these locations to limit pollution exposure based on air-quality forecasts. This is, in part, because many areas do not have air quality forecasts; and available forecasts are limited to ozone and particulate matter smaller than 2.5 microns in diameter. The forecasts also do not account for differences in terrain and air pollution sources that can lead to inaccuracies. This research enables resilience of pilot western communities by providing actionable, timely, high-resolution, air quality information on the neighborhood-scale with actionable air quality information and tools for decision makers to act on this information. This research integrates engineering innovations and community engagement by focusing on links between neighborhood-scale, automated, air quality forecasts and cost-effective, air quality measurements. It creates tools and guidance for decision makers to actively reduce short and long-term exposure to air quality hazards (i.e. ozone and particulate matter between 2.5 and 10 microns). Using cost-effective environmental sensors and smart data analysis techniques, this work empowers citizens, scientists, and policy makers to make data-driven decisions about air quality and its hazards. This is particularly relevant for under-served communities that bear a disproportionate share of air pollution environmental burdens. Broader impacts of the work not only include actionable information for improving local air quality which will benefit the health of the communities where it is employed, but also provides a rich framework for student education and sustainable job opportunities that have the potential for attracting students to fields in science, engineering, and mathematics. It also supports infrastructure and communities in Utah, which is an EPSCoR state.This research builds on existing innovations in sensing and forecasting infrastructure as well as strong civic partnerships between university researchers, the Utah Division of Air Quality, and the Utah Department of Health and Human Services. This pilot has interwoven technical, civic partnership, and team-building goals. Project deliverables include high-resolution (hourly, 4-km, horizontal resolution) and automated numerical forecasts of air pollution hazards related to ozone and air borne particulate matter in the 2.5 and 10 micron size range. The latter particles are primarily associated with winter thermal inversions, wildfires, and dust events, all of which cause serious health issues like asthma. This work will impact both urban and rural communities. The research also includes a technology development and deployment piece of novel, cost-effective, air quality sensors that are able to measure community-scale differences in the up to 10 micron-sized dust particle ranges. The data can be integrated into existing community monitoring networks. The work also provides a framework, co-developed with civic partners, that can be used by decision makers to help translate high-resolution, air quality information into action that results in the reduction of air pollution exposure to those living in western communities. If successful, the approach and technology has the potential for scaling to other locations around the nation.This project is in response to the Civic Innovation Challenge program—Track A. Living in a changing climate: pre-disaster action around adaptation, resilience, and mitigation—and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.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.

美国超过 40% 的人口（超过 1.37 亿人）生活在因颗粒物或臭氧而导致空气污染不健康的地区。空气质量较差的社区主要集中在美国西部服务匮乏的地区。由于冬季逆温、野火和沙尘暴，美国西部地区的空气质量会定期出现全国最差的情况。这些地区的个人很难根据空气质量预测来限制污染暴露。 ,部分原因是许多地区没有空气质量预报；而且可用的预报仅限于臭氧和直径小于 2.5 微米的颗粒物。这些预报也没有考虑到可能导致不准确的地形和空气污染源的差异。这项研究通过提供社区范围内可操作的、及时的、高分辨率的空气质量信息以及可供决策者根据这些信息采取行动的工具来增强西部试点社区的复原力。这项研究将工程创新与社区结合起来。通过关注社区规模的自动化空气质量预测与具有成本效益的空气质量测量之间的联系，它为决策者创建了工具和指导，以积极减少短期和长期的空气质量危害（即臭氧和颗粒物）。这项工作使用具有成本效益的环境传感器和智能数据分析技术，使公民、科学家和政策制定者能够就空气质量及其危害做出数据驱动的决策，这对于服务不足的社区尤其重要。这项工作的更广泛影响不仅包括改善当地空气质量的可操作信息，这将有利于其所在社区的健康，而且还为学生教育和可持续发展提供了丰富的框架。它还为犹他州（EPSCoR 州）的基础设施和社区提供了潜在的就业机会。这项研究建立在传感和预测基础设施方面的现有创新以及强大的公民合作伙伴关系的基础上。犹他州大学研究人员该试点项目涉及技术、公民合作和团队建设目标，包括高分辨率（每小时、4 公里、水平分辨率）和自动数值预报。与臭氧和空气中 2.5 微米和 10 微米尺寸范围内的颗粒物相关的空气污染危害主要与冬季逆温、野火和灰尘事件有关，所有这些都会导致严重的健康问题，例如。这项工作将影响城市和农村社区，该研究还包括一种新型、经济高效的空气质量传感器的技术开发和部署，该传感器能够测量社区范围内直径达 10 微米的灰尘的差异。该工作还提供了一个与民间合作伙伴共同开发的框架，可以帮助决策者将高分辨率的空气质量信息转化为行动。减少生活在西部社区的空气污染。如果成功，该方法和技术有可能扩展到全国其他地方。该项目是为了响应公民创新挑战计划 - 轨道 A。生活在不断变化的气候中：围绕适应、复原力和恢复能力的灾前行动该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Laboratory evaluation of the Alphasense OPC-N3, and the Plantower PMS5003 and PMS6003 sensors

Alphasense OPC-N3、Plantower PMS5003 和 PMS6003 传感器的实验室评估

• DOI: 10.1016/j.jaerosci.2023.106181
• 发表时间: 2023
• 期刊: Journal of Aerosol Science
• 影响因子: 4.5
• 作者: Kaur, Kamaljeet;Kelly, Kerry E.
• 通讯作者: Kelly, Kerry E.

Performance evaluation of the Alphasense OPC-N3 and Plantower PMS5003 sensor in measuring dust events in the Salt Lake Valley, Utah

• DOI: 10.5194/amt-16-2455-2023
• 发表时间: 2023-05
• 期刊: Atmospheric Measurement Techniques
• 影响因子: 3.8
• 作者: Kamaljeet Kaur;K. Kelly