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| Collaborative Research: AccelNet: Clean Air Monitoring and Solutions Network (CAMS-Net) | |
| 项目编号 | 2020677 |
| Daniel Westervelt | |
| 项目主持机构 | Columbia University |
| 开始日期 | 2021-01-01 |
| 结束日期 | 12/31/2025 |
| 英文摘要 | 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. |
| 资助机构 | US-NSF |
| 项目经费 | $964,001.00 |
| 项目类型 | Standard Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/212469 |
| 推荐引用方式 GB/T 7714 | Daniel Westervelt.Collaborative Research: AccelNet: Clean Air Monitoring and Solutions Network (CAMS-Net).2021. |
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