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Collaborative Research: AccelNet: Clean Air Monitoring and Solutions Network (CAMS-Net)

合作研究：AccelNet：清洁空气监测和解决方案网络（CAMS-Net）

基本信息

批准号：
2020666
负责人：
Albert Presto
金额：
$ 50万
依托单位：
Carnegie-Mellon University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-01-01 至 2025-12-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2020666&HistoricalAwards=false
关键词：
Collaborative Research AccelNet Clean Air

项目摘要

Air pollution is causing a global public health crisis, responsible for around 4.9 million premature deaths worldwide each year. Air pollution-related disease and death increasingly occur in places least equipped with the technical capacity, planning, and resources to address them. The Clean Air Monitoring and Solutions Network (CAMS-Net) establishes an international network of networks that unites scientists, decision-makers, city administrators, citizen groups, the private sector, and other local stakeholders in co-developing new methods and practices for real-time air quality data collection, data sharing, and solutions for air quality improvements. CAMS-Net brings together at least 32 multidisciplinary member networks from North America, Europe, Africa, and India. This AccelNet project establishes a mechanism for international collaboration, builds technical capacity, shares knowledge, and trains the next generation of air quality practitioners and advocates, including graduate students and postdoctoral researchers. A crucial component and key service to society of the network of networks is the provision of publicly available, open-access and high-quality air pollution data, which is timely because air quality is poised to degrade further in many highly populated places as climate changes and as economies grow.CAMS-Net will accelerate effective solutions for clean air by promoting novel research into a promising but largely untapped resource for cost-effective air quality monitoring. A traditional approach for improving air quality in cities is the development and implementation of a management plan, which is typically anchored by a network of high-quality, research-grade measurement devices collecting real-time data coupled with the technical expertise to analyze and make decisions based on that data. So-called low-cost sensors (LCS) have the potential to revolutionize clean air solutions and spur regulatory action, especially in lower- and middle-income countries. LCS are being deployed all over the world. Yet no global consortium exists to help standardize best practices, share deployment strategies, ensure quality control, and calibrate sensors towards research-grade quality. CAMS-Net seeks to maximize the value to science and society of the current proliferation of unknown quality data acquired by LCS through capacity building, knowledge exchange, and acceleration of novel research. CAMS-Net research directions also include applying LCS networks to evaluate air quality models, refining satellite-derived air quality products, informing the implementation of air quality standards, and estimating fine-scale pollutant exposure for health impact analyses. Students and postdoctoral researchers will participate in scholar exchanges and take on leadership roles within CAMS-Net, preparing them for careers in global air quality. CAMS-Net will create a strong, sustained global network of networks focused on closing the air pollution data and knowledge gaps.The Accelerating Research through International Network-to-Network Collaborations (AccelNet) program is designed to accelerate the process of scientific discovery and prepare the next generation of U.S. researchers for multiteam international collaborations. The AccelNet program supports strategic linkages among U.S. research networks and complementary networks abroad that will leverage research and educational resources to tackle grand scientific challenges that require significant coordinated international efforts.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.

空气污染正在引发一场全球公共卫生危机，每年导致全球约490万人过早死亡。与空气污染有关的疾病和死亡越来越多地发生在最不具备解决这些问题的技术能力、规划和资源的地方。清洁空气监测和解决方案网络（CAMS-Net）建立了一个国际网络，将科学家、决策者、城市管理者、公民团体、私营部门和其他地方利益相关者联合起来，共同开发实时空气质量数据收集、数据共享和改善空气质量解决方案的新方法和实践。CAMS-Net汇集了来自北美、欧洲、非洲和印度的至少32个多学科成员网络。该项目建立了国际合作机制，建立了技术能力，分享了知识，并培训了下一代空气质量实践者和倡导者，包括研究生和博士后研究人员。网络中的网络的一个关键组成部分和对社会的关键服务是提供可公开获得、开放获取和高质量的空气污染数据，这是及时的，因为随着气候变化和经济增长，许多人口稠密地区的空气质量将进一步恶化。CAMS-Net将通过促进对具有成本效益的空气质量监测这一有前途但在很大程度上尚未开发的资源的新研究，加速清洁空气的有效解决方案。改善城市空气质量的传统方法是制定和实施一项管理计划，该计划通常以高质量的研究级测量设备网络为基础，这些设备收集实时数据，并结合技术专长，根据这些数据进行分析和决策。所谓的低成本传感器（LCS）有可能彻底改变清洁空气的解决方案，并推动监管行动，特别是在中低收入国家。濒海战斗舰正在世界各地部署。然而，目前还没有全球性的联盟来帮助标准化最佳实践、共享部署策略、确保质量控制和校准传感器以达到研究级的质量。CAMS-Net旨在通过能力建设、知识交流和加速新研究，使LCS目前获得的未知质量数据的激增对科学和社会的价值最大化。CAMS-Net的研究方向还包括应用LCS网络评估空气质量模型，改进卫星衍生的空气质量产品，为空气质量标准的实施提供信息，以及为健康影响分析估计细尺度污染物暴露。学生和博士后研究人员将参加学者交流，并在CAMS-Net中担任领导角色，为他们在全球空气质量领域的职业生涯做好准备。CAMS-Net将建立一个强大、持续的全球网络，重点是缩小空气污染数据和知识差距。通过国际网络对网络合作加速研究（AccelNet）计划旨在加速科学发现的进程，并为下一代美国研究人员进行多团队国际合作做好准备。AccelNet项目支持美国研究网络与国外互补网络之间的战略联系，将利用研究和教育资源来应对需要重大国际协调努力的重大科学挑战。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。