CAREER: Understanding Land-Atmosphere Exchange of Reactive Nitrogen through Tiered and Machine Learning Assisted Monitoring

This proposal seeks to advance the fundamental understanding of Earth’s nitrogen cycle, with a focus on the land-atmosphere exchange of nitrogen. This research integrates field observations, land-surface and atmospheric modeling, and sensor development, establishing a foundation for large-scale monitoring and policy evaluation. The project will evaluate the use of low-cost reactive nitrogen measurements and machine learning methods for robust reactive nitrogen flux spatial interpolation. Comprehensive datasets and improved models will provide a robust scientific basis for evidence-based policy decisions in air quality regulation, agricultural nutrient management, and ecosystem conservation in the United States. This project synergistically combines direct flux measurements at "supersites" with inferential modeling that uses low-cost measurements and existing air quality observations. The objectives are to: (1) advance the fundamental understanding of atmospheric reactive nitrogen (Nr), including both reactive nitrogen oxides (NOy, sum of all oxidation products of nitrogen oxides (NOx)), total ammonium (NHx, sum of gaseous ammonia (NH3), and particulate ammonium (NH4+); (2) develop and implement innovative monitoring and modeling strategies for nitrogen management; and (3) cultivate the next generation of scientists and engineers while fostering public awareness of the importance of nitrogen management. The project includes a citizen science component that empowers students, teachers, agricultural stakeholders, and community volunteers to participate in scientific research. 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. NSF Award ID: 2542691 | Program: 01002829DB NSF RESEARCH & RELATED ACTIVIT,01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Da Pan | Institution: Georgia Tech Research Corporation, ATLANTA, GA | Award Amount: $499,431 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2542691 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2542691.html