Mason scientist aims to improve ground-level air quality prediction
Chaowei Yang, Professor, Director, NSF Spatiotemporal Innovation Center, Geography and Geoinformation Science, and his collaborators received $100,000 from NASA-Goddard Space Flight Center to improve ground-level air quality prediction by integrating new observation system data and numerical simulations to support decisions relevant to air quality in Los Angles.
As part of this project, the researchers will: 1) select, preprocess, downscale, and fuse air quality data from 10km x10km (regional climate) to 500m x 500m (street) resolution and relevant temporal resolution with LA coverage; 2) develop relevant machine learning and numerical simulation or prediction to improve data quality and accuracy; and 3) automate the data transformation, ingestion, and harmonization for cloud-computing-based management and analysis alignment with the NASA Advanced Information Systems Technology (AIST) Air Quality Analytical Center Framework (AQACF) and Apache Science Data Analytics Platform (SDAP).
The results of this research will complement the AIST AQACF effort by streamlining the generation of value-added air quality data products and analysis to improve future Earth science research and facilitate regional and local long-term air quality predictions.
Funding began in October 2021 and will end in late September 2022.