Clean Air Monitoring and Solutions Network (CAMS-Net)

CAMS-Net is aimed at advancing research on the appropriate use, best practices, and applications of low-cost air quality monitors by creating a knowledge network of networks among international experts in the field of air pollution. The use of LCS for air pollution measurement is growing rapidly. LCS have the potential to spur regulatory action in places where air quality is poor, but the accurate use and application of LCS requires careful consideration. Topics for scientific international collaborative research under CAMS-Net will include deployment strategies, calibration and correction techniques, data standardization and cleaning, and other best practices and methods. CAMS-Net research directions also include applications of LCS networks to air quality modeling, satellite-derived air quality products, implementation of air quality standards, and fine-scale exposure estimates that are needed in health impact analyses.

The research is focused on the Global South, many of the countries suffer from extreme air pollution but do not have widespread monitoring to observe and initiate action to reverse the problem. We aim to improve this lack of data by equipping and training the next generation of air pollution scientists and other practitioners within the US and abroad on best practices for LCS usage. Postdoctoral scientists, students, and early career scientists will be encouraged to take leadership roles within the working groups, and will be able to apply for seed funding to conduct independent pilot research projects. This process will help train early career researchers in the proposal-writing skills that are necessary to be successful in the scientific research and academic community.

The Clean Air Monitoring and Solutions Network (CAMS-Net) an international network of networks will link faculty, postdoctoral researchers, and students who are working on various scientific aspects of air pollution research with each other and with local stakeholders in order to meet the shared goal of improved air quality. CAMS-Net will address a major community-identified scientific challenge and also addresses at least two NSF 10 Big Ideas: Harnessing the Data Revolution and Growing Convergence Research. Low-cost sensors (LCS) for air pollution have the potential to revolutionize clean air solutions and spur regulatory action, especially in low- and middle-income countries (LMIC) of the Global South, where financial resources may be limited. LCS are lower-fidelity sensors that operate on optical or electrochemical principles and require less power and maintenance than regulatory-grade monitors. The development of new low-cost sensors is occurring rapidly and the market is booming, reminiscent of the “Wild West”. Currently, LCS are being deployed all over the world, yet currently no global consortium exists to help standardize best practices, share deployment strategies, ensure quality control, and correct sensors towards regulatory- or research-grade quality. Without careful calibration and quality control, low quality data may proliferate. The use of regulatory-grade monitors in an air quality network provides a reference for LCS calibration, giving us confidence in the information provided by LCS.

Vision and goals

The overall vision is to develop a network of international networks that provides a forum for exchange of knowledge, ideas, and data among scientists, practitioners, decision makers, and other stakeholders towards the goal of improved usage and application of low-cost sensors for air quality. Specific goals include:

1. Create an international network of networks for air pollution monitoring and clean air solutions in diverse locations in both the Global South and North;
2. Share knowledge, data, and best practices among each member network to synthesize research focused on acquiring useful, actionable open data from low cost sensors, regulatory grade monitors, satellite data, air quality models, and other sources in order to promote clean air solutions;
3. Build technical capacity on air pollution monitoring and solutions, including training of scientists including students, postdoctoral researchers, and early career researchers from a variety of partner networks and cities;
4. Facilitate an open communication channel among scholars to promote collaboration and idea exchange, including creation of an online platform and hub to establish coordination among partner networks;
5. Establish mechanisms for substantial collaboration among international partner networks on multidisciplinary research into clean air solutions and how low-cost sensors can be leveraged to deliver novel results about the composition of the air.

The project will partner with universities from the USA, Africa, Europe, Asia and other sensor manufacturers such as;

OpenAQ promotes international engagement to meet the overall goal of improved air quality. They have aggregated more than 471 million air quality measurements from 130 data sources, in 84 countries across the globe, and make the data available through a flexible API. In addition to developing the air quality data infrastructure, OpenAQ also conducts workshops on how to apply this data across the globe.

NESCAUM In the US, a nonprofit consortium providing scientific, technical, analytical, and policy support to the air quality programs of the eight Northeast states. NESCAUM is interested in promoting international engagement to meet the overall goal of improved air quality.

The Jülich Supercomputing Centre, who operate the TOAR database and combine strong air quality science expertise with cutting-edge high-performance computer and data science.

NASA partners, including the MAIA project and TEMPO, in running workshops, webinars, and training sessions on their data products for air quality, and their expertise will be a welcome addition to CAMS-Net.